diff --git a/Answers/TestingDataBinary.csv b/Answers/TestingDataBinary.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0af9dd4c51af5ed4f1d320fb162dc193767058f4
--- /dev/null
+++ b/Answers/TestingDataBinary.csv
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diff --git a/Answers/TestingDataMulti.csv b/Answers/TestingDataMulti.csv
new file mode 100644
index 0000000000000000000000000000000000000000..54853dbd41aa58698d442e9f30c303b74890120d
--- /dev/null
+++ b/Answers/TestingDataMulti.csv
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diff --git a/Answers/TestingResultsBinary.csv b/Answers/TestingResultsBinary.csv
new file mode 100644
index 0000000000000000000000000000000000000000..76d19a3688bc0292bea96dc4b808ba87a80ee5ff
--- /dev/null
+++ b/Answers/TestingResultsBinary.csv
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diff --git a/Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv b/Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv
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diff --git a/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv b/Model Results/TestingResultsBinary_LabelsOnly.csv
similarity index 100%
rename from TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
rename to Model Results/TestingResultsBinary_LabelsOnly.csv
diff --git a/Model Results/TestingResultsBinary_LinearSVC.csv b/Model Results/TestingResultsBinary_LinearSVC.csv
new file mode 100644
index 0000000000000000000000000000000000000000..60bdc3efbeeb4562469cdd5c21594da36a1273cf
--- /dev/null
+++ b/Model Results/TestingResultsBinary_LinearSVC.csv	
@@ -0,0 +1,100 @@
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diff --git a/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv b/Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
similarity index 98%
rename from TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
rename to Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
index 2ffc6db6df1bd4e8a73aa73654db6a7095805db5..76d19a3688bc0292bea96dc4b808ba87a80ee5ff 100644
--- a/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
+++ b/Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv	
@@ -21,16 +21,16 @@
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diff --git a/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv b/Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
similarity index 98%
rename from TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
rename to Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
index 2ffc6db6df1bd4e8a73aa73654db6a7095805db5..0c431a467432fb19b0233ee4c4e57d69504d24cf 100644
--- a/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
+++ b/Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv	
@@ -21,16 +21,16 @@
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diff --git a/Model Results/TestingResultsMulti_DecisionTreeClassifier.csv b/Model Results/TestingResultsMulti_DecisionTreeClassifier.csv
new file mode 100644
index 0000000000000000000000000000000000000000..53f35a19d514aada5b02d221c973342efa17a541
--- /dev/null
+++ b/Model Results/TestingResultsMulti_DecisionTreeClassifier.csv	
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diff --git a/Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier.csv b/Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fbec2fb92b6a9ebd7f6fa763e74c63aa6a6cc974
--- /dev/null
+++ b/Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier.csv	
@@ -0,0 +1,100 @@
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diff --git a/Model Results/TestingResultsMulti_KNeighbors.csv b/Model Results/TestingResultsMulti_KNeighbors.csv
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diff --git a/Model Results/TestingResultsMulti_LinearSVC.csv b/Model Results/TestingResultsMulti_LinearSVC.csv
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diff --git a/Model Results/TestingResultsMulti_RandomizedSearchKNeighborsClassifier.csv b/Model Results/TestingResultsMulti_RandomizedSearchKNeighborsClassifier.csv
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diff --git a/Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifier.csv b/Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifier.csv
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diff --git a/Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv b/Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..79040ddd8ad517932bb2e8ccee5ab5f4d255cbbc
--- /dev/null
+++ b/Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv	
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diff --git a/Model Results/TestingResultsMulti_RandomizedSearchSVC.csv b/Model Results/TestingResultsMulti_RandomizedSearchSVC.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1c9fc3557c53447c987ad66e028c52b6fb031b2f
--- /dev/null
+++ b/Model Results/TestingResultsMulti_RandomizedSearchSVC.csv	
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diff --git a/Model Results/TestingResultsMulti_SVCrbf.csv b/Model Results/TestingResultsMulti_SVCrbf.csv
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index 0000000000000000000000000000000000000000..3fa1685e4ff4827ee6f34604cbd7d4e97392d965
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diff --git a/Model Results/TestingResultsMulti_SVCsigmoid_LabelsOnly.csv b/Model Results/TestingResultsMulti_SVCsigmoid_LabelsOnly.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1a78e4574fff855361897f1e7e5204cc454811d6
--- /dev/null
+++ b/Model Results/TestingResultsMulti_SVCsigmoid_LabelsOnly.csv	
@@ -0,0 +1,100 @@
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diff --git a/TrainingDataBinary.csv b/Model Results/TrainingDataBinary.csv
similarity index 100%
rename from TrainingDataBinary.csv
rename to Model Results/TrainingDataBinary.csv
diff --git a/TrainingDataBinaryWithHeaders.csv b/Model Results/TrainingDataBinaryWithHeaders.csv
similarity index 100%
rename from TrainingDataBinaryWithHeaders.csv
rename to Model Results/TrainingDataBinaryWithHeaders.csv
diff --git a/Program Outputs/Part_A_Output_CV.txt b/Program Outputs/Part_A_Output_CV.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c758be0760d577c5280bef63d7eda5c0e572034f
--- /dev/null
+++ b/Program Outputs/Part_A_Output_CV.txt	
@@ -0,0 +1,132 @@
+Loading Config for TASK A
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+Cross Validating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, GridSearchSVC, RandomizedSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Creating LogisticRegression
+Creating LogisticRegressionliblinear
+Creating LinearSVC
+Creating KNeighbors
+Creating SVCrbf
+Creating SVCsigmoid
+Creating DecisionTreeClassifier
+Creating RandomForestClassifier
+Creating GridSearchSVC
+Fitting GridSearchSVC
+Creating and Tuning Models:  64%|██████▍   | 9/14 [17:20<09:38, 115.65s/it]GridSearchSVC best parameters: 
+{'C': 10, 'gamma': 1, 'kernel': 'linear'}
+GridSearchSVC best estimator: 
+SVC(C=10, gamma=1, kernel='linear')
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9041666666666666
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.9262407407407407
+Creating RandomizedSearchSVC
+Fitting RandomizedSearchSVC
+Creating and Tuning Models:  71%|███████▏  | 10/14 [20:02<08:07, 121.92s/it]RandomizedSearchSVC best parameters: 
+{'kernel': 'linear', 'gamma': 1, 'C': 100}
+RandomizedSearchSVC best estimator: 
+SVC(C=100, gamma=1, kernel='linear')
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.8985
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.9345185185185185
+Creating RandomizedSearchRandomForestClassifier
+Fitting RandomizedSearchRandomForestClassifier
+Creating and Tuning Models:  79%|███████▊  | 11/14 [22:41<06:23, 127.96s/it]RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 200, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_depth': 10, 'bootstrap': True}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(max_depth=10, n_estimators=200)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.8881666666666665
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9725925925925925
+Creating RandomizedSearchRandomForestClassifierV2
+Fitting RandomizedSearchRandomForestClassifierV2
+RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 1800, 'min_samples_split': 10, 'min_samples_leaf': 2, 'max_features': None, 'max_depth': 20, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(max_depth=20, max_features=None, min_samples_leaf=2,
+                       min_samples_split=10, n_estimators=1800)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.881
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9964259259259258
+Creating RandomizedSearchKNeighborsClassifier
+Fitting RandomizedSearchKNeighborsClassifier
+Creating and Tuning Models:  93%|█████████▎| 13/14 [39:08<03:49, 229.81s/it]RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'distance', 'p': 2, 'n_neighbors': 16}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(n_neighbors=16, weights='distance')
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.7266666666666667
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Creating GridSearchKNeighborsClassifier
+Fitting GridSearchKNeighborsClassifier
+Creating and Tuning Models: 100%|██████████| 14/14 [39:23<00:00, 168.84s/it]
+Models:   0%|          | 0/14 [00:00<?, ?it/s]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]GridSearchKNeighborsClassifier best parameters: 
+{'n_neighbors': 5, 'p': 2, 'weights': 'distance'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(weights='distance')
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.738
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Cross Validating and comparing the following model(s): LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, GridSearchSVC, RandomizedSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Mean cross-validation accuracy for LogisticRegression: 0.8713333333333333
+
+Scoring Metrics:  50%|█████     | 1/2 [00:01<00:01,  1.50s/it]
+Scoring Metrics: 100%|██████████| 2/2 [00:03<00:00,  1.50s/it]
+Models:   7%|▋         | 1/14 [00:03<00:39,  3.00s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]Mean cross-validation f1 for LogisticRegression: 0.8628680287964172
+Mean cross-validation accuracy for LogisticRegressionliblinear: 0.8700000000000001
+
+Scoring Metrics:  50%|█████     | 1/2 [00:06<00:06,  6.49s/it]
+Scoring Metrics: 100%|██████████| 2/2 [00:12<00:00,  6.46s/it]
+Models:  14%|█▍        | 2/14 [00:15<01:46,  8.85s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]Mean cross-validation f1 for LogisticRegressionliblinear: 0.8607051625209758
+Mean cross-validation accuracy for LinearSVC: 0.893
+
+Scoring Metrics:  50%|█████     | 1/2 [01:05<01:05, 65.51s/it]
+Mean cross-validation f1 for LinearSVC: 0.8885910885349977
+Scoring Metrics: 100%|██████████| 2/2 [02:11<00:00, 65.88s/it]
+Models:  21%|██▏       | 3/14 [02:27<11:54, 64.92s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Mean cross-validation accuracy for KNeighbors: 0.7346666666666668
+Scoring Metrics:  50%|█████     | 1/2 [00:00<00:00,  1.48it/s]
+Mean cross-validation f1 for KNeighbors: 0.730498346757627
+Scoring Metrics: 100%|██████████| 2/2 [00:01<00:00,  1.58it/s]
+Models:  29%|██▊       | 4/14 [02:28<06:37, 39.80s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Scoring Metrics:  50%|█████     | 1/2 [00:07<00:07,  7.92s/it]Mean cross-validation accuracy for SVCrbf: 0.8711666666666666
+Mean cross-validation f1 for SVCrbf: 0.8659685632768908
+
+Scoring Metrics: 100%|██████████| 2/2 [00:15<00:00,  7.87s/it]
+Models:  36%|███▌      | 5/14 [02:44<04:40, 31.13s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Mean cross-validation accuracy for SVCsigmoid: 0.6871666666666666
+Scoring Metrics:  50%|█████     | 1/2 [00:06<00:06,  6.58s/it]
+Mean cross-validation f1 for SVCsigmoid: 0.685997097294721
+Scoring Metrics: 100%|██████████| 2/2 [00:13<00:00,  6.58s/it]
+Models:  43%|████▎     | 6/14 [02:57<03:20, 25.02s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Scoring Metrics:  50%|█████     | 1/2 [00:03<00:03,  3.61s/it]Mean cross-validation accuracy for DecisionTreeClassifier: 0.8541666666666666
+Mean cross-validation f1 for DecisionTreeClassifier: 0.8526968282225145
+
+Scoring Metrics: 100%|██████████| 2/2 [00:07<00:00,  3.66s/it]
+Models:  50%|█████     | 7/14 [03:05<02:14, 19.23s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Mean cross-validation accuracy for RandomForestClassifier: 0.8738333333333334
+Scoring Metrics:  50%|█████     | 1/2 [03:44<03:44, 224.93s/it]
+Mean cross-validation f1 for RandomForestClassifier: 0.8750209793564571
+Scoring Metrics: 100%|██████████| 2/2 [07:29<00:00, 224.60s/it]
+Models:  57%|█████▋    | 8/14 [10:34<15:36, 156.14s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]
+Mean cross-validation accuracy for GridSearchSVC: 0.9041666666666666
+Scoring Metrics:  50%|█████     | 1/2 [00:46<00:46, 46.97s/it]
+Scoring Metrics: 100%|██████████| 2/2 [01:33<00:00, 46.97s/it]
+Models:  64%|██████▍   | 9/14 [12:08<11:23, 136.69s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]Mean cross-validation f1 for GridSearchSVC: 0.9026770116280082
+
+Scoring Metrics:  50%|█████     | 1/2 [05:05<05:05, 305.23s/it]Mean cross-validation accuracy for RandomizedSearchSVC: 0.8985
+
+Scoring Metrics: 100%|██████████| 2/2 [10:12<00:00, 306.15s/it]
+Models:  71%|███████▏  | 10/14 [22:20<18:53, 283.44s/it]
+Scoring Metrics:   0%|          | 0/2 [00:00<?, ?it/s]Mean cross-validation f1 for RandomizedSearchSVC: 0.896523398097604
+
+Scoring Metrics:  50%|█████     | 1/2 [00:29<00:29, 29.34s/it]Mean cross-validation accuracy for RandomizedSearchRandomForestClassifier: 0.885
+Mean cross-validation f1 for RandomizedSearchRandomForestClassifier: 0.8912382233805454
diff --git a/Program Outputs/Part_A_Output_No_CV.txt b/Program Outputs/Part_A_Output_No_CV.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e7cbc39bd51ca84e1119915aa7f10d839b33a2c2
--- /dev/null
+++ b/Program Outputs/Part_A_Output_No_CV.txt	
@@ -0,0 +1,552 @@
+Loading Config for TASK A
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+Evaluating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, GridSearchSVC, RandomizedSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Models:   0%|          | 0/14 [00:00<?, ?it/s]Validation Accuracy Score for LogisticRegression: 0.8716666666666667
+Classification Report for LogisticRegression_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.83      0.94      0.88       300
+           1       0.93      0.81      0.86       300
+
+    accuracy                           0.87       600
+   macro avg       0.88      0.87      0.87       600
+weighted avg       0.88      0.87      0.87       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegression: 0.8866666666666667
+Testing Precision Score for LogisticRegression: 0.9233576642335767
+Testing Recall Score for LogisticRegression: 0.8433333333333334
+Classification Report for LogisticRegression_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.92      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for LogisticRegression in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.92      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Models:   7%|▋         | 1/14 [00:00<00:05,  2.23it/s]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for LogisticRegressionliblinear: 0.87
+Classification Report for LogisticRegressionliblinear_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.83      0.94      0.88       300
+           1       0.93      0.80      0.86       300
+
+    accuracy                           0.87       600
+   macro avg       0.88      0.87      0.87       600
+weighted avg       0.88      0.87      0.87       600
+
+  warnings.warn(msg, category=FutureWarning)
+Models:  14%|█▍        | 2/14 [00:01<00:08,  1.47it/s]Testing Accuracy Score for LogisticRegressionliblinear: 0.8883333333333333
+Testing Precision Score for LogisticRegressionliblinear: 0.9267399267399268
+Testing Recall Score for LogisticRegressionliblinear: 0.8433333333333334
+Classification Report for LogisticRegressionliblinear_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.93      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for LogisticRegressionliblinear in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.93      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Validation Accuracy Score for LinearSVC: 0.8933333333333333
+Classification Report for LinearSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.87      0.93      0.90       300
+           1       0.92      0.86      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.90      0.89      0.89       600
+weighted avg       0.90      0.89      0.89       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LinearSVC: 0.9
+Testing Precision Score for LinearSVC: 0.9195804195804196
+Testing Recall Score for LinearSVC: 0.8766666666666667
+Classification Report for LinearSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.88      0.92      0.90       300
+           1       0.92      0.88      0.90       300
+
+    accuracy                           0.90       600
+   macro avg       0.90      0.90      0.90       600
+weighted avg       0.90      0.90      0.90       600
+
+Classification Report for LinearSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.88      0.92      0.90       300
+           1       0.92      0.88      0.90       300
+
+    accuracy                           0.90       600
+   macro avg       0.90      0.90      0.90       600
+weighted avg       0.90      0.90      0.90       600
+
+Models:  21%|██▏       | 3/14 [00:06<00:32,  2.97s/it]Validation Accuracy Score for KNeighbors: 0.9316666666666666
+Classification Report for KNeighbors_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.97      0.93       300
+           1       0.97      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for KNeighbors: 0.9283333333333333
+Testing Precision Score for KNeighbors: 0.9605734767025089
+Testing Recall Score for KNeighbors: 0.8933333333333333
+Classification Report for KNeighbors_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.96      0.93       300
+           1       0.96      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+Classification Report for KNeighbors in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.96      0.93       300
+           1       0.96      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+Models:  29%|██▊       | 4/14 [00:07<00:20,  2.08s/it]Validation Accuracy Score for SVCrbf: 0.8766666666666667
+Classification Report for SVCrbf_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.85      0.91      0.88       300
+           1       0.91      0.84      0.87       300
+
+    accuracy                           0.88       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.88      0.88      0.88       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCrbf: 0.8916666666666667
+Testing Precision Score for SVCrbf: 0.924187725631769
+Testing Recall Score for SVCrbf: 0.8533333333333334
+Classification Report for SVCrbf_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.90       300
+           1       0.92      0.85      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for SVCrbf in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.90       300
+           1       0.92      0.85      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Models:  36%|███▌      | 5/14 [00:09<00:17,  1.97s/it]Validation Accuracy Score for SVCsigmoid: 0.715
+Classification Report for SVCsigmoid_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.70      0.74      0.72       300
+           1       0.73      0.69      0.71       300
+
+    accuracy                           0.71       600
+   macro avg       0.72      0.71      0.71       600
+weighted avg       0.72      0.71      0.71       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCsigmoid: 0.6916666666666667
+Testing Precision Score for SVCsigmoid: 0.698961937716263
+Testing Recall Score for SVCsigmoid: 0.6733333333333333
+Classification Report for SVCsigmoid_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.68      0.71      0.70       300
+           1       0.70      0.67      0.69       300
+
+    accuracy                           0.69       600
+   macro avg       0.69      0.69      0.69       600
+weighted avg       0.69      0.69      0.69       600
+
+Models:  43%|████▎     | 6/14 [00:10<00:13,  1.72s/it]Classification Report for SVCsigmoid in Part A:
+              precision    recall  f1-score   support
+
+           0       0.68      0.71      0.70       300
+           1       0.70      0.67      0.69       300
+
+    accuracy                           0.69       600
+   macro avg       0.69      0.69      0.69       600
+weighted avg       0.69      0.69      0.69       600
+
+Validation Accuracy Score for DecisionTreeClassifier: 0.97
+Classification Report for DecisionTreeClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.97      0.97      0.97       300
+           1       0.97      0.97      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for DecisionTreeClassifier: 0.9666666666666667
+Testing Precision Score for DecisionTreeClassifier: 0.9794520547945206
+Testing Recall Score for DecisionTreeClassifier: 0.9533333333333334
+Classification Report for DecisionTreeClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.98      0.97       300
+           1       0.98      0.95      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+Classification Report for DecisionTreeClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.98      0.97       300
+           1       0.98      0.95      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+Models:  50%|█████     | 7/14 [00:11<00:09,  1.36s/it]Validation Accuracy Score for RandomForestClassifier: 0.9966666666666667
+Classification Report for RandomForestClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      1.00       300
+           1       1.00      0.99      1.00       300
+
+    accuracy                           1.00       600
+   macro avg       1.00      1.00      1.00       600
+weighted avg       1.00      1.00      1.00       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomForestClassifier: 0.99
+Testing Precision Score for RandomForestClassifier: 0.9867549668874173
+Testing Recall Score for RandomForestClassifier: 0.9933333333333333
+Classification Report for RandomForestClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Models:  57%|█████▋    | 8/14 [00:32<00:45,  7.65s/it]Classification Report for RandomForestClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+GridSearchSVC best parameters: 
+{'C': 1000, 'gamma': 0.1, 'kernel': 'rbf'}
+GridSearchSVC best estimator: 
+SVC(C=1000, gamma=0.1)
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9525
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.9991666666666666
+Validation Accuracy Score for GridSearchSVC: 0.9616666666666667
+Classification Report for GridSearchSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchSVC: 0.9516666666666667
+Testing Precision Score for GridSearchSVC: 0.9413680781758957
+Testing Recall Score for GridSearchSVC: 0.9633333333333334
+Classification Report for GridSearchSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.94      0.96      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for GridSearchSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.94      0.96      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+Models:  64%|██████▍   | 9/14 [03:26<04:58, 59.66s/it]RandomizedSearchSVC best parameters: 
+{'kernel': 'rbf', 'gamma': 0.1, 'C': 100}
+RandomizedSearchSVC best estimator: 
+SVC(C=100, gamma=0.1)
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.9424999999999999
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.9903124999999999
+Validation Accuracy Score for RandomizedSearchSVC: 0.9566666666666667
+Classification Report for RandomizedSearchSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.94      0.97      0.96       300
+           1       0.97      0.94      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchSVC: 0.945
+Testing Precision Score for RandomizedSearchSVC: 0.9435215946843853
+Testing Recall Score for RandomizedSearchSVC: 0.9466666666666667
+Classification Report for RandomizedSearchSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.94      0.95      0.95       300
+
+    accuracy                           0.94       600
+   macro avg       0.95      0.95      0.94       600
+weighted avg       0.95      0.94      0.94       600
+
+Models:  71%|███████▏  | 10/14 [05:36<05:25, 81.46s/it]Classification Report for RandomizedSearchSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.94      0.95      0.95       300
+
+    accuracy                           0.94       600
+   macro avg       0.95      0.95      0.94       600
+weighted avg       0.95      0.94      0.94       600
+
+RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 1400, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_depth': 110, 'bootstrap': False}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(bootstrap=False, max_depth=110, n_estimators=1400)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9808333333333333
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9966666666666667
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      1.00       300
+           1       1.00      0.99      1.00       300
+
+    accuracy                           1.00       600
+   macro avg       1.00      1.00      1.00       600
+weighted avg       1.00      1.00      1.00       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifier: 0.99
+Testing Precision Score for RandomizedSearchRandomForestClassifier: 0.9867549668874173
+Testing Recall Score for RandomizedSearchRandomForestClassifier: 0.9933333333333333
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Models:  79%|███████▊  | 11/14 [06:51<03:58, 79.52s/it]Classification Report for RandomizedSearchRandomForestClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 1200, 'min_samples_split': 5, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': None, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(min_samples_leaf=2, min_samples_split=5,
+                       n_estimators=1200)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9695833333333334
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9986458333333333
+Validation Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.99
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9833333333333333
+Testing Precision Score for RandomizedSearchRandomForestClassifierV2: 0.9833333333333333
+Testing Recall Score for RandomizedSearchRandomForestClassifierV2: 0.9833333333333333
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.98      0.98      0.98       300
+
+    accuracy                           0.98       600
+   macro avg       0.98      0.98      0.98       600
+weighted avg       0.98      0.98      0.98       600
+
+Classification Report for RandomizedSearchRandomForestClassifierV2 in Part A:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.98      0.98      0.98       300
+
+    accuracy                           0.98       600
+   macro avg       0.98      0.98      0.98       600
+weighted avg       0.98      0.98      0.98       600
+
+Models:  86%|████████▌ | 12/14 [11:30<04:40, 140.20s/it]RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'distance', 'p': 2, 'n_neighbors': 12}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(n_neighbors=12, weights='distance')
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.9241666666666667
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.955
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.93      0.98      0.96       300
+           1       0.98      0.93      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.96      0.95      0.95       600
+weighted avg       0.96      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.93
+Testing Precision Score for RandomizedSearchKNeighborsClassifier: 0.9479166666666666
+Testing Recall Score for RandomizedSearchKNeighborsClassifier: 0.91
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.91      0.95      0.93       300
+           1       0.95      0.91      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+Classification Report for RandomizedSearchKNeighborsClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.91      0.95      0.93       300
+           1       0.95      0.91      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+Models:  93%|█████████▎| 13/14 [11:33<01:38, 98.60s/it] GridSearchKNeighborsClassifier best parameters: 
+{'n_neighbors': 5, 'p': 1, 'weights': 'distance'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(p=1, weights='distance')
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.9514583333333334
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for GridSearchKNeighborsClassifier: 0.9766666666666667
+Classification Report for GridSearchKNeighborsClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.97      0.99      0.98       300
+           1       0.99      0.97      0.98       300
+
+    accuracy                           0.98       600
+   macro avg       0.98      0.98      0.98       600
+weighted avg       0.98      0.98      0.98       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchKNeighborsClassifier: 0.9633333333333334
+Testing Precision Score for GridSearchKNeighborsClassifier: 0.9727891156462585
+Testing Recall Score for GridSearchKNeighborsClassifier: 0.9533333333333334
+Classification Report for GridSearchKNeighborsClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+Models: 100%|██████████| 14/14 [11:37<00:00, 49.79s/it]
+Classification Report for GridSearchKNeighborsClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+Remember this is for PART: A
\ No newline at end of file
diff --git a/Program Outputs/Part_A_Output_No_CV_2.txt b/Program Outputs/Part_A_Output_No_CV_2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cf870991ff3967fe4aaaadd8594070d2d3211431
--- /dev/null
+++ b/Program Outputs/Part_A_Output_No_CV_2.txt	
@@ -0,0 +1,710 @@
+Loading Config for TASK A
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+Evaluating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, GridSearchSVC, RandomizedSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Models:   0%|          | 0/14 [00:00<?, ?it/s]Validation Accuracy Score for LogisticRegression: 0.8716666666666667
+Classification Report for LogisticRegression_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.83      0.94      0.88       300
+           1       0.93      0.81      0.86       300
+
+    accuracy                           0.87       600
+   macro avg       0.88      0.87      0.87       600
+weighted avg       0.88      0.87      0.87       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegression: 0.8866666666666667
+Testing Precision Score for LogisticRegression: 0.9233576642335767
+Testing Recall Score for LogisticRegression: 0.8433333333333334
+Classification Report for LogisticRegression_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.92      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for LogisticRegression in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.92      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0
+ 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    58
+1    42
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegression_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_LogisticRegression.csv
+Saved Dataframe to: TestingResultsBinary_LogisticRegression_LabelsOnly.csv
+Models:   7%|▋         | 1/14 [00:00<00:12,  1.04it/s]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for LogisticRegressionliblinear: 0.87
+Classification Report for LogisticRegressionliblinear_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.83      0.94      0.88       300
+           1       0.93      0.80      0.86       300
+
+    accuracy                           0.87       600
+   macro avg       0.88      0.87      0.87       600
+weighted avg       0.88      0.87      0.87       600
+
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegressionliblinear: 0.8883333333333333
+Testing Precision Score for LogisticRegressionliblinear: 0.9267399267399268
+Testing Recall Score for LogisticRegressionliblinear: 0.8433333333333334
+Classification Report for LogisticRegressionliblinear_Against_Test_Set in Part A:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.93      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for LogisticRegressionliblinear in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.89       300
+           1       0.93      0.84      0.88       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0
+ 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    58
+1    42
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegressionliblinear_Part_A_Result_Distribution.png
+Models:  14%|█▍        | 2/14 [00:02<00:14,  1.22s/it]Saved Dataframe to: TestingResultsBinary_LogisticRegressionliblinear.csv
+Saved Dataframe to: TestingResultsBinary_LogisticRegressionliblinear_LabelsOnly.csv
+Validation Accuracy Score for LinearSVC: 0.8933333333333333
+Classification Report for LinearSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.87      0.93      0.90       300
+           1       0.92      0.86      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.90      0.89      0.89       600
+weighted avg       0.90      0.89      0.89       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LinearSVC: 0.9
+Testing Precision Score for LinearSVC: 0.9195804195804196
+Testing Recall Score for LinearSVC: 0.8766666666666667
+Classification Report for LinearSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.88      0.92      0.90       300
+           1       0.92      0.88      0.90       300
+
+    accuracy                           0.90       600
+   macro avg       0.90      0.90      0.90       600
+weighted avg       0.90      0.90      0.90       600
+
+Classification Report for LinearSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.88      0.92      0.90       300
+           1       0.92      0.88      0.90       300
+
+    accuracy                           0.90       600
+   macro avg       0.90      0.90      0.90       600
+weighted avg       0.90      0.90      0.90       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1
+ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1]
+1    60
+0    40
+Name: Label, dtype: int64
+Saved distribution plot to: LinearSVC_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_LinearSVC.csv
+Saved Dataframe to: TestingResultsBinary_LinearSVC_LabelsOnly.csv
+Models:  21%|██▏       | 3/14 [00:08<00:36,  3.35s/it]Validation Accuracy Score for KNeighbors: 0.9316666666666666
+Classification Report for KNeighbors_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.97      0.93       300
+           1       0.97      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for KNeighbors: 0.9283333333333333
+Testing Precision Score for KNeighbors: 0.9605734767025089
+Testing Recall Score for KNeighbors: 0.8933333333333333
+Classification Report for KNeighbors_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.96      0.93       300
+           1       0.96      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+Classification Report for KNeighbors in Part A:
+              precision    recall  f1-score   support
+
+           0       0.90      0.96      0.93       300
+           1       0.96      0.89      0.93       300
+
+    accuracy                           0.93       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.93      0.93      0.93       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0
+ 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1
+ 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]
+0    54
+1    46
+Name: Label, dtype: int64
+Saved distribution plot to: KNeighbors_Part_A_Result_Distribution.png
+Models:  29%|██▊       | 4/14 [00:09<00:25,  2.54s/it]Saved Dataframe to: TestingResultsBinary_KNeighbors.csv
+Saved Dataframe to: TestingResultsBinary_KNeighbors_LabelsOnly.csv
+Validation Accuracy Score for SVCrbf: 0.8766666666666667
+Classification Report for SVCrbf_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.85      0.91      0.88       300
+           1       0.91      0.84      0.87       300
+
+    accuracy                           0.88       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.88      0.88      0.88       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCrbf: 0.8916666666666667
+Testing Precision Score for SVCrbf: 0.924187725631769
+Testing Recall Score for SVCrbf: 0.8533333333333334
+Classification Report for SVCrbf_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.90       300
+           1       0.92      0.85      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+Classification Report for SVCrbf in Part A:
+              precision    recall  f1-score   support
+
+           0       0.86      0.93      0.90       300
+           1       0.92      0.85      0.89       300
+
+    accuracy                           0.89       600
+   macro avg       0.89      0.89      0.89       600
+weighted avg       0.89      0.89      0.89       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0
+ 0 0 1 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 1
+ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    56
+1    44
+Name: Label, dtype: int64
+Saved distribution plot to: SVCrbf_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_SVCrbf.csv
+Saved Dataframe to: TestingResultsBinary_SVCrbf_LabelsOnly.csv
+Models:  36%|███▌      | 5/14 [00:11<00:22,  2.45s/it]Validation Accuracy Score for SVCsigmoid: 0.715
+Classification Report for SVCsigmoid_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.70      0.74      0.72       300
+           1       0.73      0.69      0.71       300
+
+    accuracy                           0.71       600
+   macro avg       0.72      0.71      0.71       600
+weighted avg       0.72      0.71      0.71       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCsigmoid: 0.6916666666666667
+Testing Precision Score for SVCsigmoid: 0.698961937716263
+Testing Recall Score for SVCsigmoid: 0.6733333333333333
+Classification Report for SVCsigmoid_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.68      0.71      0.70       300
+           1       0.70      0.67      0.69       300
+
+    accuracy                           0.69       600
+   macro avg       0.69      0.69      0.69       600
+weighted avg       0.69      0.69      0.69       600
+
+Classification Report for SVCsigmoid in Part A:
+              precision    recall  f1-score   support
+
+           0       0.68      0.71      0.70       300
+           1       0.70      0.67      0.69       300
+
+    accuracy                           0.69       600
+   macro avg       0.69      0.69      0.69       600
+weighted avg       0.69      0.69      0.69       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 0
+ 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    68
+1    32
+Name: Label, dtype: int64
+Saved distribution plot to: SVCsigmoid_Part_A_Result_Distribution.png
+Models:  43%|████▎     | 6/14 [00:13<00:17,  2.21s/it]Saved Dataframe to: TestingResultsBinary_SVCsigmoid.csv
+Saved Dataframe to: TestingResultsBinary_SVCsigmoid_LabelsOnly.csv
+Validation Accuracy Score for DecisionTreeClassifier: 0.9683333333333334
+Classification Report for DecisionTreeClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.98      0.97       300
+           1       0.98      0.96      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for DecisionTreeClassifier: 0.9666666666666667
+Testing Precision Score for DecisionTreeClassifier: 0.9761904761904762
+Testing Recall Score for DecisionTreeClassifier: 0.9566666666666667
+Classification Report for DecisionTreeClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.98      0.97       300
+           1       0.98      0.96      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+Classification Report for DecisionTreeClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.98      0.97       300
+           1       0.98      0.96      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.97      0.97      0.97       600
+weighted avg       0.97      0.97      0.97       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 1 1 0 0 0 1 1 1 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 1 1]
+1    64
+0    36
+Name: Label, dtype: int64
+Saved distribution plot to: DecisionTreeClassifier_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_DecisionTreeClassifier.csv
+Models:  50%|█████     | 7/14 [00:14<00:13,  1.86s/it]Saved Dataframe to: TestingResultsBinary_DecisionTreeClassifier_LabelsOnly.csv
+Validation Accuracy Score for RandomForestClassifier: 0.9966666666666667
+Classification Report for RandomForestClassifier_Against_Validation_Set in Part A:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      1.00       300
+           1       1.00      0.99      1.00       300
+
+    accuracy                           1.00       600
+   macro avg       1.00      1.00      1.00       600
+weighted avg       1.00      1.00      1.00       600
+
+Testing Accuracy Score for RandomForestClassifier: 0.99
+Testing Precision Score for RandomForestClassifier: 0.9867549668874173
+Testing Recall Score for RandomForestClassifier: 0.9933333333333333
+Classification Report for RandomForestClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Classification Report for RandomForestClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 1 0 0 1 0
+ 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 0]
+1    74
+0    26
+Name: Label, dtype: int64
+Saved distribution plot to: RandomForestClassifier_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomForestClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomForestClassifier_LabelsOnly.csv
+Models:  57%|█████▋    | 8/14 [00:37<00:50,  8.37s/it]GridSearchSVC best parameters: 
+{'C': 1000, 'gamma': 0.1, 'kernel': 'rbf'}
+GridSearchSVC best estimator: 
+SVC(C=1000, gamma=0.1)
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9525
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.9991666666666666
+Validation Accuracy Score for GridSearchSVC: 0.9616666666666667
+Classification Report for GridSearchSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchSVC: 0.9516666666666667
+Testing Precision Score for GridSearchSVC: 0.9413680781758957
+Testing Recall Score for GridSearchSVC: 0.9633333333333334
+Classification Report for GridSearchSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.94      0.96      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for GridSearchSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.94      0.96      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0]
+1    82
+0    18
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchSVC_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_GridSearchSVC.csv
+Saved Dataframe to: TestingResultsBinary_GridSearchSVC_LabelsOnly.csv
+Models:  64%|██████▍   | 9/14 [03:37<05:11, 62.28s/it]RandomizedSearchSVC best parameters: 
+{'kernel': 'rbf', 'gamma': 0.1, 'C': 100}
+RandomizedSearchSVC best estimator: 
+SVC(C=100, gamma=0.1)
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.9424999999999999
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.9903124999999999
+Validation Accuracy Score for RandomizedSearchSVC: 0.9566666666666667
+Classification Report for RandomizedSearchSVC_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.94      0.97      0.96       300
+           1       0.97      0.94      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchSVC: 0.945
+Testing Precision Score for RandomizedSearchSVC: 0.9435215946843853
+Testing Recall Score for RandomizedSearchSVC: 0.9466666666666667
+Classification Report for RandomizedSearchSVC_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.94      0.95      0.95       300
+
+    accuracy                           0.94       600
+   macro avg       0.95      0.95      0.94       600
+weighted avg       0.95      0.94      0.94       600
+
+Classification Report for RandomizedSearchSVC in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.94      0.95      0.95       300
+
+    accuracy                           0.94       600
+   macro avg       0.95      0.95      0.94       600
+weighted avg       0.95      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0]
+1    75
+0    25
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchSVC_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchSVC.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchSVC_LabelsOnly.csv
+Models:  71%|███████▏  | 10/14 [05:53<05:40, 85.03s/it]RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 2000, 'min_samples_split': 2, 'min_samples_leaf': 2, 'max_depth': 30, 'bootstrap': False}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(bootstrap=False, max_depth=30, min_samples_leaf=2,
+                       n_estimators=2000)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9810416666666667
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9966666666666667
+E:\Documents\Github\comp3217-2023-cw2\utils.py:273: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
+  fig, ax = plt.subplots(figsize=(figsize_x, figsize_y))
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      1.00       300
+           1       1.00      0.99      1.00       300
+
+    accuracy                           1.00       600
+   macro avg       1.00      1.00      1.00       600
+weighted avg       1.00      1.00      1.00       600
+
+Testing Accuracy Score for RandomizedSearchRandomForestClassifier: 0.99
+Testing Precision Score for RandomizedSearchRandomForestClassifier: 0.9867549668874173
+Testing Recall Score for RandomizedSearchRandomForestClassifier: 0.9933333333333333
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Classification Report for RandomizedSearchRandomForestClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1 0
+ 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 0]
+1    76
+0    24
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifier_Part_A_Result_Distribution.png
+Models:  79%|███████▊  | 11/14 [07:31<04:26, 88.99s/it]Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifier_LabelsOnly.csv
+RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 400, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_features': 'sqrt', 'max_depth': 20, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(max_depth=20, n_estimators=400)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9752083333333333
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9933333333333333
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      0.99       300
+           1       1.00      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9883333333333333
+Testing Precision Score for RandomizedSearchRandomForestClassifierV2: 0.9867109634551495
+Testing Recall Score for RandomizedSearchRandomForestClassifierV2: 0.99
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Classification Report for RandomizedSearchRandomForestClassifierV2 in Part A:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.99      0.99      0.99       300
+
+    accuracy                           0.99       600
+   macro avg       0.99      0.99      0.99       600
+weighted avg       0.99      0.99      0.99       600
+
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 1 0 1 1 1 1
+ 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 1 0
+ 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 0]
+1    74
+0    26
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifierV2_Part_A_Result_Distribution.png
+Models:  86%|████████▌ | 12/14 [10:02<03:35, 107.84s/it]Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
+RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'distance', 'p': 2, 'n_neighbors': 5}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(weights='distance')
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.941875
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.975
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.96      0.99      0.98       300
+           1       0.99      0.96      0.97       300
+
+    accuracy                           0.97       600
+   macro avg       0.98      0.98      0.97       600
+weighted avg       0.98      0.97      0.97       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.95
+Testing Precision Score for RandomizedSearchKNeighborsClassifier: 0.9655172413793104
+Testing Recall Score for RandomizedSearchKNeighborsClassifier: 0.9333333333333333
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.94      0.97      0.95       300
+           1       0.97      0.93      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomizedSearchKNeighborsClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.94      0.97      0.95       300
+           1       0.97      0.93      0.95       300
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0
+ 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1
+ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]
+0    59
+1    41
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchKNeighborsClassifier_Part_A_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
+Models:  93%|█████████▎| 13/14 [10:05<01:16, 76.06s/it] GridSearchKNeighborsClassifier best parameters: 
+{'n_neighbors': 5, 'p': 1, 'weights': 'distance'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(p=1, weights='distance')
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.9514583333333334
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for GridSearchKNeighborsClassifier: 0.9766666666666667
+Classification Report for GridSearchKNeighborsClassifier_Against_Validation_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.97      0.99      0.98       300
+           1       0.99      0.97      0.98       300
+
+    accuracy                           0.98       600
+   macro avg       0.98      0.98      0.98       600
+weighted avg       0.98      0.98      0.98       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchKNeighborsClassifier: 0.9633333333333334
+Testing Precision Score for GridSearchKNeighborsClassifier: 0.9727891156462585
+Testing Recall Score for GridSearchKNeighborsClassifier: 0.9533333333333334
+Classification Report for GridSearchKNeighborsClassifier_Against_Test_Set in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+Classification Report for GridSearchKNeighborsClassifier in Part A:
+              precision    recall  f1-score   support
+
+           0       0.95      0.97      0.96       300
+           1       0.97      0.95      0.96       300
+
+    accuracy                           0.96       600
+   macro avg       0.96      0.96      0.96       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 0 0
+ 0 0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1
+ 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1]
+0    69
+1    31
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchKNeighborsClassifier_Part_A_Result_Distribution.png
+Models: 100%|██████████| 14/14 [10:09<00:00, 43.53s/it]
+Saved Dataframe to: TestingResultsBinary_GridSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsBinary_GridSearchKNeighborsClassifier_LabelsOnly.csv
+Remember this is for PART: A
+
+Process finished with exit code 0
\ No newline at end of file
diff --git a/Program Outputs/Part_B_Output_No_CV.txt b/Program Outputs/Part_B_Output_No_CV.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8dac092a4ad8a5568f145e5a442e1da0f7bfe716
--- /dev/null
+++ b/Program Outputs/Part_B_Output_No_CV.txt	
@@ -0,0 +1,769 @@
+C:\Users\uwu\miniconda3\envs\comp3217\python.exe E:\Documents\Github\comp3217-2023-cw2\main.py
+Loading Config for TASK B
+SMOTE-ing Data
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+Evaluating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, RandomizedSearchSVC, GridSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Models:   0%|          | 0/14 [00:00<?, ?it/s]Validation Accuracy Score for LogisticRegression: 0.6625971143174251
+Classification Report for LogisticRegression_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.75      0.93      0.83       300
+           1       0.63      0.51      0.57       300
+           2       0.57      0.55      0.56       301
+
+    accuracy                           0.66       901
+   macro avg       0.65      0.66      0.65       901
+weighted avg       0.65      0.66      0.65       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegression: 0.6577777777777778
+Testing Precision Score for LogisticRegression: 0.6577777777777778
+Testing Recall Score for LogisticRegression: 0.6577777777777778
+Classification Report for LogisticRegression_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.78      0.90      0.84       300
+           1       0.62      0.50      0.55       300
+           2       0.55      0.57      0.56       300
+
+    accuracy                           0.66       900
+   macro avg       0.65      0.66      0.65       900
+weighted avg       0.65      0.66      0.65       900
+
+Classification Report for LogisticRegression in Part B:
+              precision    recall  f1-score   support
+
+           0       0.78      0.90      0.84       300
+           1       0.62      0.50      0.55       300
+           2       0.55      0.57      0.56       300
+
+    accuracy                           0.66       900
+   macro avg       0.65      0.66      0.65       900
+weighted avg       0.65      0.66      0.65       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 0 2 2 0 0 2 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 2 2 2 2 1 0 2 1 2 2 1 2 1 1 1 1 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 1 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0]
+0    42
+1    30
+2    28
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegression_Part_B_Result_Distribution.png
+Models:   7%|▋         | 1/14 [00:01<00:24,  1.89s/it]Saved Dataframe to: TestingResultsBinary_LogisticRegression.csv
+Saved Dataframe to: TestingResultsBinary_LogisticRegression_LabelsOnly.csv
+Validation Accuracy Score for LogisticRegressionliblinear: 0.660377358490566
+Classification Report for LogisticRegressionliblinear_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.73      0.93      0.82       300
+           1       0.64      0.51      0.57       300
+           2       0.59      0.54      0.56       301
+
+    accuracy                           0.66       901
+   macro avg       0.65      0.66      0.65       901
+weighted avg       0.65      0.66      0.65       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegressionliblinear: 0.6444444444444445
+Testing Precision Score for LogisticRegressionliblinear: 0.6444444444444445
+Testing Recall Score for LogisticRegressionliblinear: 0.6444444444444445
+Classification Report for LogisticRegressionliblinear_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.76      0.91      0.83       300
+           1       0.60      0.49      0.54       300
+           2       0.54      0.53      0.54       300
+
+    accuracy                           0.64       900
+   macro avg       0.63      0.64      0.63       900
+weighted avg       0.63      0.64      0.63       900
+
+Classification Report for LogisticRegressionliblinear in Part B:
+              precision    recall  f1-score   support
+
+           0       0.76      0.91      0.83       300
+           1       0.60      0.49      0.54       300
+           2       0.54      0.53      0.54       300
+
+    accuracy                           0.64       900
+   macro avg       0.63      0.64      0.63       900
+weighted avg       0.63      0.64      0.63       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 0 2 2 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 0 2 2 2 0 0 2 1 2 2 1 2 1 1 1 1 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 0 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0]
+0    44
+1    29
+2    27
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegressionliblinear_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_LogisticRegressionliblinear.csv
+Saved Dataframe to: TestingResultsBinary_LogisticRegressionliblinear_LabelsOnly.csv
+Models:  14%|█▍        | 2/14 [00:06<00:40,  3.41s/it]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for LinearSVC: 0.6781354051054383
+Classification Report for LinearSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.75      0.93      0.83       300
+           1       0.65      0.56      0.60       300
+           2       0.60      0.55      0.57       301
+
+    accuracy                           0.68       901
+   macro avg       0.67      0.68      0.67       901
+weighted avg       0.67      0.68      0.67       901
+
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LinearSVC: 0.6566666666666666
+Testing Precision Score for LinearSVC: 0.6566666666666666
+Testing Recall Score for LinearSVC: 0.6566666666666666
+Classification Report for LinearSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.78      0.91      0.84       300
+           1       0.61      0.53      0.56       300
+           2       0.55      0.54      0.54       300
+
+    accuracy                           0.66       900
+   macro avg       0.65      0.66      0.65       900
+weighted avg       0.65      0.66      0.65       900
+
+Classification Report for LinearSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.78      0.91      0.84       300
+           1       0.61      0.53      0.56       300
+           2       0.55      0.54      0.54       300
+
+    accuracy                           0.66       900
+   macro avg       0.65      0.66      0.65       900
+weighted avg       0.65      0.66      0.65       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 0 2 2 2 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 2 0 0 2 1 2 0 0 0 0 2 2 2 2 1 2 1 1 1 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    47
+1    27
+2    26
+Name: Label, dtype: int64
+Saved distribution plot to: LinearSVC_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_LinearSVC.csv
+Saved Dataframe to: TestingResultsBinary_LinearSVC_LabelsOnly.csv
+Models:  21%|██▏       | 3/14 [02:43<13:29, 73.62s/it]Validation Accuracy Score for KNeighbors: 0.9056603773584906
+Classification Report for KNeighbors_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.94      0.94      0.94       300
+           1       0.90      0.86      0.88       300
+           2       0.88      0.91      0.90       301
+
+    accuracy                           0.91       901
+   macro avg       0.91      0.91      0.91       901
+weighted avg       0.91      0.91      0.91       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for KNeighbors: 0.9055555555555556
+Testing Precision Score for KNeighbors: 0.9055555555555556
+Testing Recall Score for KNeighbors: 0.9055555555555556
+Classification Report for KNeighbors_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.94      0.95       300
+           1       0.90      0.87      0.88       300
+           2       0.85      0.91      0.88       300
+
+    accuracy                           0.91       900
+   macro avg       0.91      0.91      0.91       900
+weighted avg       0.91      0.91      0.91       900
+
+Classification Report for KNeighbors in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.94      0.95       300
+           1       0.90      0.87      0.88       300
+           2       0.85      0.91      0.88       300
+
+    accuracy                           0.91       900
+   macro avg       0.91      0.91      0.91       900
+weighted avg       0.91      0.91      0.91       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 1 2 0 1 0 0 0 0 1 0 0 0 0 0 0 2 2 1 2
+ 2 1 0 0 0 1 1 2 0 0 1 2 1 1 2 2 2 2 1 1 1 0 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    40
+1    38
+2    22
+Name: Label, dtype: int64
+Saved distribution plot to: KNeighbors_Part_B_Result_Distribution.png
+Models:  29%|██▊       | 4/14 [02:44<07:30, 45.02s/it]Saved Dataframe to: TestingResultsBinary_KNeighbors.csv
+Saved Dataframe to: TestingResultsBinary_KNeighbors_LabelsOnly.csv
+Validation Accuracy Score for SVCrbf: 0.7180910099889012
+Classification Report for SVCrbf_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.75      0.92      0.83       300
+           1       0.70      0.64      0.67       300
+           2       0.69      0.59      0.64       301
+
+    accuracy                           0.72       901
+   macro avg       0.71      0.72      0.71       901
+weighted avg       0.71      0.72      0.71       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCrbf: 0.6977777777777778
+Testing Precision Score for SVCrbf: 0.6977777777777778
+Testing Recall Score for SVCrbf: 0.6977777777777778
+Classification Report for SVCrbf_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.75      0.91      0.83       300
+           1       0.69      0.62      0.65       300
+           2       0.63      0.56      0.59       300
+
+    accuracy                           0.70       900
+   macro avg       0.69      0.70      0.69       900
+weighted avg       0.69      0.70      0.69       900
+
+Classification Report for SVCrbf in Part B:
+              precision    recall  f1-score   support
+
+           0       0.75      0.91      0.83       300
+           1       0.69      0.62      0.65       300
+           2       0.63      0.56      0.59       300
+
+    accuracy                           0.70       900
+   macro avg       0.69      0.70      0.69       900
+weighted avg       0.69      0.70      0.69       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 2 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 0 0 1 0 2 2 2 1 0 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 2 2 2 2 2 0 0 0 0 0 0 0 0 0]
+1    39
+0    38
+2    23
+Name: Label, dtype: int64
+Saved distribution plot to: SVCrbf_Part_B_Result_Distribution.png
+Models:  36%|███▌      | 5/14 [03:02<05:15, 35.10s/it]Saved Dataframe to: TestingResultsBinary_SVCrbf.csv
+Saved Dataframe to: TestingResultsBinary_SVCrbf_LabelsOnly.csv
+Validation Accuracy Score for SVCsigmoid: 0.45615982241953384
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Classification Report for SVCsigmoid_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.58      0.55      0.57       300
+           1       0.40      0.48      0.43       300
+           2       0.40      0.33      0.36       301
+
+    accuracy                           0.46       901
+   macro avg       0.46      0.46      0.46       901
+weighted avg       0.46      0.46      0.46       901
+
+Testing Accuracy Score for SVCsigmoid: 0.47333333333333333
+Testing Precision Score for SVCsigmoid: 0.47333333333333333
+Testing Recall Score for SVCsigmoid: 0.47333333333333333
+Classification Report for SVCsigmoid_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.55      0.59      0.57       300
+           1       0.42      0.46      0.44       300
+           2       0.45      0.37      0.40       300
+
+    accuracy                           0.47       900
+   macro avg       0.47      0.47      0.47       900
+weighted avg       0.47      0.47      0.47       900
+
+Classification Report for SVCsigmoid in Part B:
+              precision    recall  f1-score   support
+
+           0       0.55      0.59      0.57       300
+           1       0.42      0.46      0.44       300
+           2       0.45      0.37      0.40       300
+
+    accuracy                           0.47       900
+   macro avg       0.47      0.47      0.47       900
+weighted avg       0.47      0.47      0.47       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 2 0 0 2 2 1 1 1 0 0 1 1 1 1 1 2 2 2 2 1 1 1 2 2 2 2 2 2 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 2 1 1 1 0 1 1 1 1]
+1    45
+0    39
+2    16
+Name: Label, dtype: int64
+Saved distribution plot to: SVCsigmoid_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_SVCsigmoid.csv
+Saved Dataframe to: TestingResultsBinary_SVCsigmoid_LabelsOnly.csv
+Models:  43%|████▎     | 6/14 [03:16<03:42, 27.87s/it]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for DecisionTreeClassifier: 0.9245283018867925
+Classification Report for DecisionTreeClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.95      0.96      0.96       300
+           1       0.91      0.89      0.90       300
+           2       0.90      0.92      0.91       301
+
+    accuracy                           0.92       901
+   macro avg       0.92      0.92      0.92       901
+weighted avg       0.92      0.92      0.92       901
+
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for DecisionTreeClassifier: 0.91
+Testing Precision Score for DecisionTreeClassifier: 0.91
+Testing Recall Score for DecisionTreeClassifier: 0.91
+Classification Report for DecisionTreeClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.90      0.90      0.90       300
+           2       0.87      0.89      0.88       300
+
+    accuracy                           0.91       900
+   macro avg       0.91      0.91      0.91       900
+weighted avg       0.91      0.91      0.91       900
+
+Classification Report for DecisionTreeClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.90      0.90      0.90       300
+           2       0.87      0.89      0.88       300
+
+    accuracy                           0.91       900
+   macro avg       0.91      0.91      0.91       900
+weighted avg       0.91      0.91      0.91       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 2 2 2 2 2 2 1 1 1 1
+ 1 2 1 1 0 2 1 2 0 0 2 0 1 0 0 0 2 2 2 2 1 2 2 1 1 1 1 1 1 1 1 1 0 0 1 1 1
+ 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1]
+1    48
+2    28
+0    24
+Name: Label, dtype: int64
+Saved distribution plot to: DecisionTreeClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_DecisionTreeClassifier.csv
+Saved Dataframe to: TestingResultsBinary_DecisionTreeClassifier_LabelsOnly.csv
+Models:  50%|█████     | 7/14 [03:17<02:14, 19.20s/it]Validation Accuracy Score for RandomForestClassifier: 0.9755826859045506
+Classification Report for RandomForestClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      1.00       300
+           1       0.97      0.96      0.96       300
+           2       0.97      0.97      0.97       301
+
+    accuracy                           0.98       901
+   macro avg       0.98      0.98      0.98       901
+weighted avg       0.98      0.98      0.98       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomForestClassifier: 0.97
+Testing Precision Score for RandomForestClassifier: 0.97
+Testing Recall Score for RandomForestClassifier: 0.97
+Classification Report for RandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.96      0.96      0.96       300
+           2       0.96      0.96      0.96       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+Classification Report for RandomForestClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.96      0.96      0.96       300
+           2       0.96      0.96      0.96       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 1 2 2 1 1 1 1 1 1 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 2 1 0 1 1 1 2 2 1 2 2 2 2 2 1 2 2 2 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+1    41
+0    35
+2    24
+Name: Label, dtype: int64
+Saved distribution plot to: RandomForestClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomForestClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomForestClassifier_LabelsOnly.csv
+Models:  57%|█████▋    | 8/14 [03:55<02:30, 25.14s/it]RandomizedSearchSVC best parameters: 
+{'kernel': 'rbf', 'gamma': 0.1, 'C': 100}
+RandomizedSearchSVC best estimator: 
+SVC(C=100, gamma=0.1, probability=True)
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.9308236649529897
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.9913877891227338
+Validation Accuracy Score for RandomizedSearchSVC: 0.946725860155383
+Classification Report for RandomizedSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.95      0.96       300
+           1       0.93      0.94      0.94       300
+           2       0.95      0.94      0.95       301
+
+    accuracy                           0.95       901
+   macro avg       0.95      0.95      0.95       901
+weighted avg       0.95      0.95      0.95       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchSVC: 0.95
+Testing Precision Score for RandomizedSearchSVC: 0.95
+Testing Recall Score for RandomizedSearchSVC: 0.95
+Classification Report for RandomizedSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.95      0.96       300
+           1       0.92      0.97      0.94       300
+           2       0.96      0.93      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+Classification Report for RandomizedSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.95      0.96       300
+           1       0.92      0.97      0.94       300
+           2       0.96      0.93      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 1 1 1 0 1 1 1 1 0 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 1 1 1 1 0 0 0 0]
+1    47
+0    36
+2    17
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchSVC_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchSVC.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchSVC_LabelsOnly.csv
+Models:  64%|██████▍   | 9/14 [04:43<02:41, 32.34s/it]GridSearchSVC best parameters: 
+{'C': 100, 'gamma': 0.1, 'kernel': 'rbf'}
+GridSearchSVC best estimator: 
+SVC(C=100, gamma=0.1, probability=True)
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9308236649529897
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.9913877891227338
+Validation Accuracy Score for GridSearchSVC: 0.946725860155383
+Classification Report for GridSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.95      0.96       300
+           1       0.93      0.94      0.94       300
+           2       0.95      0.94      0.95       301
+
+    accuracy                           0.95       901
+   macro avg       0.95      0.95      0.95       901
+weighted avg       0.95      0.95      0.95       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchSVC: 0.95
+Testing Precision Score for GridSearchSVC: 0.95
+Testing Recall Score for GridSearchSVC: 0.95
+Classification Report for GridSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.95      0.96       300
+           1       0.92      0.97      0.94       300
+           2       0.96      0.93      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+Classification Report for GridSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.95      0.96       300
+           1       0.92      0.97      0.94       300
+           2       0.96      0.93      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 1 1 1 0 1 1 1 1 0 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 1 1 1 1 0 0 0 0]
+1    47
+0    36
+2    17
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchSVC_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_GridSearchSVC.csv
+Saved Dataframe to: TestingResultsBinary_GridSearchSVC_LabelsOnly.csv
+Models:  71%|███████▏  | 10/14 [06:01<03:06, 46.55s/it]RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 2000, 'min_samples_split': 5, 'min_samples_leaf': 1, 'max_depth': 40, 'bootstrap': False}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(bootstrap=False, max_depth=40, min_samples_split=5,
+                       n_estimators=2000)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9656895234125331
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9733629300776915
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      0.99       300
+           1       0.97      0.96      0.96       300
+           2       0.96      0.97      0.97       301
+
+    accuracy                           0.97       901
+   macro avg       0.97      0.97      0.97       901
+weighted avg       0.97      0.97      0.97       901
+
+E:\Documents\Github\comp3217-2023-cw2\utils.py:274: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
+  fig, ax = plt.subplots(figsize=(figsize_x, figsize_y))
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9655555555555555
+Testing Precision Score for RandomizedSearchRandomForestClassifier: 0.9655555555555555
+Testing Recall Score for RandomizedSearchRandomForestClassifier: 0.9655555555555555
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.95      0.95      0.95       300
+           2       0.95      0.96      0.95       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+Classification Report for RandomizedSearchRandomForestClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.95      0.95      0.95       300
+           2       0.95      0.96      0.95       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 1 2 2 1 1 1 1 1 1 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 2 1 0 1 1 1 2 2 1 2 2 2 2 2 1 2 2 2 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+1    41
+0    35
+2    24
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifier_Part_B_Result_Distribution.png
+Models:  79%|███████▊  | 11/14 [08:49<04:10, 83.61s/it]Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifier_LabelsOnly.csv
+RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 1000, 'min_samples_split': 2, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 100, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(max_depth=100, max_features='log2', min_samples_leaf=2,
+                       n_estimators=1000)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9566602982724284
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9983331741566529
+Validation Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9667036625971143
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      1.00      0.99       300
+           1       0.96      0.95      0.95       300
+           2       0.96      0.96      0.96       301
+
+    accuracy                           0.97       901
+   macro avg       0.97      0.97      0.97       901
+weighted avg       0.97      0.97      0.97       901
+
+Testing Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9633333333333334
+Testing Precision Score for RandomizedSearchRandomForestClassifierV2: 0.9633333333333334
+Testing Recall Score for RandomizedSearchRandomForestClassifierV2: 0.9633333333333334
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.98      0.99       300
+           1       0.95      0.95      0.95       300
+           2       0.95      0.95      0.95       300
+
+    accuracy                           0.96       900
+   macro avg       0.96      0.96      0.96       900
+weighted avg       0.96      0.96      0.96       900
+
+Classification Report for RandomizedSearchRandomForestClassifierV2 in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.98      0.99       300
+           1       0.95      0.95      0.95       300
+           2       0.95      0.95      0.95       300
+
+    accuracy                           0.96       900
+   macro avg       0.96      0.96      0.96       900
+weighted avg       0.96      0.96      0.96       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 2 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 2 1 0 1 1 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+1    39
+0    35
+2    26
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifierV2_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
+Models:  86%|████████▌ | 12/14 [14:01<05:06, 153.14s/it]RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'distance', 'p': 1, 'n_neighbors': 4}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(n_neighbors=4, p=1, weights='distance')
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.9447154485665323
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.9578246392896781
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.98      0.98       300
+           1       0.96      0.93      0.94       300
+           2       0.94      0.96      0.95       301
+
+    accuracy                           0.96       901
+   macro avg       0.96      0.96      0.96       901
+weighted avg       0.96      0.96      0.96       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.9522222222222222
+Testing Precision Score for RandomizedSearchKNeighborsClassifier: 0.9522222222222222
+Testing Recall Score for RandomizedSearchKNeighborsClassifier: 0.9522222222222222
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.96      0.97       300
+           1       0.95      0.93      0.94       300
+           2       0.93      0.96      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+Classification Report for RandomizedSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.96      0.97       300
+           1       0.95      0.93      0.94       300
+           2       0.93      0.96      0.94       300
+
+    accuracy                           0.95       900
+   macro avg       0.95      0.95      0.95       900
+weighted avg       0.95      0.95      0.95       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 1 1 2 2 2 1 2 2 1 2 2 2 2 1 1 1 0 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    41
+1    31
+2    28
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Models:  93%|█████████▎| 13/14 [14:08<01:48, 108.97s/it]Saved Dataframe to: TestingResultsBinary_RandomizedSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsBinary_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
+GridSearchKNeighborsClassifier best parameters: 
+{'leaf_size': 20, 'metric': 'manhattan', 'n_neighbors': 1, 'weights': 'uniform'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(leaf_size=20, metric='manhattan', n_neighbors=1)
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.958327775461998
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for GridSearchKNeighborsClassifier: 0.9655937846836848
+Classification Report for GridSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.97      0.94      0.95       300
+           2       0.94      0.97      0.96       301
+
+    accuracy                           0.97       901
+   macro avg       0.97      0.97      0.97       901
+weighted avg       0.97      0.97      0.97       901
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchKNeighborsClassifier: 0.9666666666666667
+Testing Precision Score for GridSearchKNeighborsClassifier: 0.9666666666666667
+Testing Recall Score for GridSearchKNeighborsClassifier: 0.9666666666666667
+Classification Report for GridSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.98      0.98       300
+           1       0.96      0.95      0.96       300
+           2       0.95      0.97      0.96       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+Classification Report for GridSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.98      0.98       300
+           1       0.96      0.95      0.96       300
+           2       0.95      0.97      0.96       300
+
+    accuracy                           0.97       900
+   macro avg       0.97      0.97      0.97       900
+weighted avg       0.97      0.97      0.97       900
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 0 1 1 2 2 1 2 2 1 2 2 2 2 1 1 1 0 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    41
+1    31
+2    28
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Models: 100%|██████████| 14/14 [14:55<00:00, 63.97s/it]
+Saved Dataframe to: TestingResultsBinary_GridSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsBinary_GridSearchKNeighborsClassifier_LabelsOnly.csv
+Remember this is for PART: B
+
+Process finished with exit code 0
diff --git a/Program Outputs/Part_B_Output_No_CV2.txt b/Program Outputs/Part_B_Output_No_CV2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0aeda6dfa13a4fabfb6ed44c76dac62acc4ba77f
--- /dev/null
+++ b/Program Outputs/Part_B_Output_No_CV2.txt	
@@ -0,0 +1,768 @@
+C:\Users\uwu\miniconda3\envs\comp3217\python.exe E:\Documents\Github\comp3217-2023-cw2\main.py
+Loading Config for TASK B
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+SMOTE-ing Test Data
+Models:   0%|          | 0/14 [00:00<?, ?it/s]Evaluating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, RandomizedSearchSVC, GridSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Validation Accuracy Score for LogisticRegression: 0.7266666666666667
+Classification Report for LogisticRegression_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.86      0.90      0.88       300
+           1       0.61      0.55      0.58       150
+           2       0.56      0.56      0.56       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegression: 0.6716666666666666
+Testing Precision Score for LogisticRegression: 0.6716666666666666
+Testing Recall Score for LogisticRegression: 0.6716666666666666
+Classification Report for LogisticRegression_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.53      0.46      0.49       150
+           2       0.42      0.41      0.42       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.67      0.66       600
+
+Classification Report for LogisticRegression in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.53      0.46      0.49       150
+           2       0.42      0.41      0.42       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.67      0.66       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 0 1 1 0 2 1 2 2 2 1 0 2 1 1 1 1 2 1 1 1 2 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    44
+1    41
+2    15
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegression_Part_B_Result_Distribution.png
+Models:   7%|▋         | 1/14 [00:01<00:24,  1.91s/it]Saved Dataframe to: TestingResultsMulti_LogisticRegression.csv
+Saved Dataframe to: TestingResultsMulti_LogisticRegression_LabelsOnly.csv
+Validation Accuracy Score for LogisticRegressionliblinear: 0.7266666666666667
+Classification Report for LogisticRegressionliblinear_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.90      0.87       300
+           1       0.62      0.53      0.57       150
+           2       0.57      0.57      0.57       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegressionliblinear: 0.6733333333333333
+Testing Precision Score for LogisticRegressionliblinear: 0.6733333333333333
+Testing Recall Score for LogisticRegressionliblinear: 0.6733333333333333
+Classification Report for LogisticRegressionliblinear_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.82      0.92      0.87       300
+           1       0.57      0.47      0.52       150
+           2       0.41      0.38      0.40       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.65      0.67      0.66       600
+
+Classification Report for LogisticRegressionliblinear in Part B:
+              precision    recall  f1-score   support
+
+           0       0.82      0.92      0.87       300
+           1       0.57      0.47      0.52       150
+           2       0.41      0.38      0.40       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.65      0.67      0.66       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 0 2 2 2 0 0 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 0 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0]
+0    44
+1    33
+2    23
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegressionliblinear_Part_B_Result_Distribution.png
+Models:  14%|█▍        | 2/14 [00:05<00:37,  3.09s/it]Saved Dataframe to: TestingResultsMulti_LogisticRegressionliblinear.csv
+Saved Dataframe to: TestingResultsMulti_LogisticRegressionliblinear_LabelsOnly.csv
+Validation Accuracy Score for LinearSVC: 0.7316666666666667
+Classification Report for LinearSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.87      0.92      0.89       300
+           1       0.60      0.53      0.57       150
+           2       0.56      0.56      0.56       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.73       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LinearSVC: 0.675
+Testing Precision Score for LinearSVC: 0.675
+Testing Recall Score for LinearSVC: 0.675
+Classification Report for LinearSVC_Against_Test_Set in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.83      0.92      0.87       300
+           1       0.55      0.46      0.50       150
+           2       0.42      0.40      0.41       150
+
+    accuracy                           0.68       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.68      0.66       600
+
+Classification Report for LinearSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.83      0.92      0.87       300
+           1       0.55      0.46      0.50       150
+           2       0.42      0.40      0.41       150
+
+    accuracy                           0.68       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.68      0.66       600
+
+Final Predictions: [1 1 1 0 0 0 1 1 1 1 1 2 2 2 2 2 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 0 2 0 0 2 1 0 0 0 0 0 1 1 1 1 1 2 1 1 1 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    55
+1    34
+2    11
+Name: Label, dtype: int64
+Saved distribution plot to: LinearSVC_Part_B_Result_Distribution.png
+Models:  21%|██▏       | 3/14 [02:12<10:54, 59.52s/it]Saved Dataframe to: TestingResultsMulti_LinearSVC.csv
+Saved Dataframe to: TestingResultsMulti_LinearSVC_LabelsOnly.csv
+Validation Accuracy Score for KNeighbors: 0.8683333333333333
+Classification Report for KNeighbors_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.92      0.94      0.93       300
+           1       0.89      0.77      0.82       150
+           2       0.75      0.83      0.79       150
+
+    accuracy                           0.87       600
+   macro avg       0.85      0.85      0.85       600
+weighted avg       0.87      0.87      0.87       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for KNeighbors: 0.8833333333333333
+Testing Precision Score for KNeighbors: 0.8833333333333333
+Testing Recall Score for KNeighbors: 0.8833333333333333
+Classification Report for KNeighbors_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.84      0.80      0.82       150
+           2       0.79      0.85      0.82       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.89      0.88      0.88       600
+
+Classification Report for KNeighbors in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.84      0.80      0.82       150
+           2       0.79      0.85      0.82       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.89      0.88      0.88       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 2 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1
+ 1 1 0 0 0 1 1 2 0 0 1 2 1 0 2 2 2 2 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 2 2 0 1 1 1 1 0 0 0 0]
+0    42
+1    38
+2    20
+Name: Label, dtype: int64
+Saved distribution plot to: KNeighbors_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_KNeighbors.csv
+Saved Dataframe to: TestingResultsMulti_KNeighbors_LabelsOnly.csv
+Models:  29%|██▊       | 4/14 [02:13<06:04, 36.45s/it]Validation Accuracy Score for SVCrbf: 0.7583333333333333
+Classification Report for SVCrbf_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.86      0.90      0.88       300
+           1       0.68      0.61      0.64       150
+           2       0.61      0.62      0.62       150
+
+    accuracy                           0.76       600
+   macro avg       0.72      0.71      0.71       600
+weighted avg       0.75      0.76      0.76       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCrbf: 0.7283333333333334
+Testing Precision Score for SVCrbf: 0.7283333333333334
+Testing Recall Score for SVCrbf: 0.7283333333333334
+Classification Report for SVCrbf_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.67      0.57      0.62       150
+           2       0.53      0.51      0.52       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+Classification Report for SVCrbf in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.67      0.57      0.62       150
+           2       0.53      0.51      0.52       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+Final Predictions: [1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 2 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 0 2 2 2 1 0 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0]
+1    39
+0    37
+2    24
+Name: Label, dtype: int64
+Saved distribution plot to: SVCrbf_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_SVCrbf.csv
+Saved Dataframe to: TestingResultsMulti_SVCrbf_LabelsOnly.csv
+Models:  36%|███▌      | 5/14 [02:29<04:22, 29.12s/it]Validation Accuracy Score for SVCsigmoid: 0.49333333333333335
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Classification Report for SVCsigmoid_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.80      0.53      0.64       300
+           1       0.34      0.52      0.41       150
+           2       0.34      0.39      0.36       150
+
+    accuracy                           0.49       600
+   macro avg       0.49      0.48      0.47       600
+weighted avg       0.57      0.49      0.51       600
+
+Testing Accuracy Score for SVCsigmoid: 0.48333333333333334
+Testing Precision Score for SVCsigmoid: 0.48333333333333334
+Testing Recall Score for SVCsigmoid: 0.48333333333333334
+Classification Report for SVCsigmoid_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.80      0.55      0.65       300
+           1       0.33      0.51      0.40       150
+           2       0.30      0.32      0.31       150
+
+    accuracy                           0.48       600
+   macro avg       0.48      0.46      0.45       600
+weighted avg       0.56      0.48      0.50       600
+
+Classification Report for SVCsigmoid in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.80      0.55      0.65       300
+           1       0.33      0.51      0.40       150
+           2       0.30      0.32      0.31       150
+
+    accuracy                           0.48       600
+   macro avg       0.48      0.46      0.45       600
+weighted avg       0.56      0.48      0.50       600
+
+Final Predictions: [2 2 2 2 2 2 1 1 1 1 1 2 2 2 2 2 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 2 0 0 2 0 1 1 1 2 0 1 1 1 1 1 0 2 2 2 1 2 1 2 2 2 2 2 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 0 2 1 2 2 2 2 2 0 1 1 1 1 1 1 1 1]
+1    46
+2    30
+0    24
+Name: Label, dtype: int64
+Saved distribution plot to: SVCsigmoid_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_SVCsigmoid.csv
+Saved Dataframe to: TestingResultsMulti_SVCsigmoid_LabelsOnly.csv
+Models:  43%|████▎     | 6/14 [02:42<03:08, 23.61s/it]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for DecisionTreeClassifier: 0.8883333333333333
+Classification Report for DecisionTreeClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.93      0.96      0.95       300
+           1       0.86      0.81      0.83       150
+           2       0.83      0.82      0.83       150
+
+    accuracy                           0.89       600
+   macro avg       0.87      0.86      0.87       600
+weighted avg       0.89      0.89      0.89       600
+
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for DecisionTreeClassifier: 0.8966666666666666
+Testing Precision Score for DecisionTreeClassifier: 0.8966666666666666
+Testing Recall Score for DecisionTreeClassifier: 0.8966666666666666
+Classification Report for DecisionTreeClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.93      0.95      0.94       300
+           1       0.88      0.84      0.86       150
+           2       0.84      0.84      0.84       150
+
+    accuracy                           0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+
+Classification Report for DecisionTreeClassifier in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.93      0.95      0.94       300
+           1       0.88      0.84      0.86       150
+           2       0.84      0.84      0.84       150
+
+    accuracy                           0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 2 2 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 0 0 1 2 2 2 2 1 2 2 1 1 0 0 2 2 0 0 2 1 1 1 1 1 1 1 1 1 0 0 1 1 1
+ 1 2 2 1 1 1 1 1 1 0 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1]
+1    71
+0    15
+2    14
+Name: Label, dtype: int64
+Saved distribution plot to: DecisionTreeClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_DecisionTreeClassifier.csv
+Saved Dataframe to: TestingResultsMulti_DecisionTreeClassifier_LabelsOnly.csv
+Models:  50%|█████     | 7/14 [02:43<01:54, 16.31s/it]Validation Accuracy Score for RandomForestClassifier: 0.96
+Classification Report for RandomForestClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.96      0.91      0.94       150
+           2       0.90      0.95      0.93       150
+
+    accuracy                           0.96       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomForestClassifier: 0.9533333333333334
+Testing Precision Score for RandomForestClassifier: 0.9533333333333334
+Testing Recall Score for RandomForestClassifier: 0.9533333333333334
+Classification Report for RandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.91      0.92       150
+           2       0.92      0.93      0.93       150
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomForestClassifier in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.91      0.92       150
+           2       0.92      0.93      0.93       150
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 2 2 1 1 0 0 0 1 0 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 1 1 0 1 1 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+0    39
+1    38
+2    23
+Name: Label, dtype: int64
+Saved distribution plot to: RandomForestClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomForestClassifier.csv
+Saved Dataframe to: TestingResultsMulti_RandomForestClassifier_LabelsOnly.csv
+Models:  57%|█████▋    | 8/14 [03:20<02:17, 22.92s/it]RandomizedSearchSVC best parameters: 
+{'kernel': 'rbf', 'gamma': 0.1, 'C': 100}
+RandomizedSearchSVC best estimator: 
+SVC(C=100, gamma=0.1, probability=True)
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.9301388888888887
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.991111111111111
+Validation Accuracy Score for RandomizedSearchSVC: 0.895
+Classification Report for RandomizedSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.86      0.87      0.86       150
+           2       0.83      0.83      0.83       150
+
+    accuracy                           0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchSVC: 0.9166666666666666
+Testing Precision Score for RandomizedSearchSVC: 0.9166666666666666
+Testing Recall Score for RandomizedSearchSVC: 0.9166666666666666
+Classification Report for RandomizedSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+Classification Report for RandomizedSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 0 1 1 1 0 0 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 0 1 1 0 0 0 0 0 0]
+1    48
+0    40
+2    12
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchSVC_Part_B_Result_Distribution.png
+Models:  64%|██████▍   | 9/14 [04:06<02:29, 29.91s/it]Saved Dataframe to: TestingResultsMulti_RandomizedSearchSVC.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchSVC_LabelsOnly.csv
+GridSearchSVC best parameters: 
+{'C': 100, 'gamma': 0.1, 'kernel': 'rbf'}
+GridSearchSVC best estimator: 
+SVC(C=100, gamma=0.1, probability=True)
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9301388888888887
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.991111111111111
+Validation Accuracy Score for GridSearchSVC: 0.895
+Classification Report for GridSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.86      0.87      0.86       150
+           2       0.83      0.83      0.83       150
+
+    accuracy                           0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchSVC: 0.9166666666666666
+Testing Precision Score for GridSearchSVC: 0.9166666666666666
+Testing Recall Score for GridSearchSVC: 0.9166666666666666
+Classification Report for GridSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+Classification Report for GridSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 0 1 1 1 0 0 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 0 1 1 0 0 0 0 0 0]
+1    48
+0    40
+2    12
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchSVC_Part_B_Result_Distribution.png
+Models:  71%|███████▏  | 10/14 [05:13<02:45, 41.50s/it]Saved Dataframe to: TestingResultsMulti_GridSearchSVC.csv
+Saved Dataframe to: TestingResultsMulti_GridSearchSVC_LabelsOnly.csv
+RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 400, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_depth': 30, 'bootstrap': True}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(max_depth=30, n_estimators=400)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9636111111111112
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9533333333333334
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Validation_Set in Part B:
+E:\Documents\Github\comp3217-2023-cw2\utils.py:264: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
+  fig, ax = plt.subplots(figsize=(figsize_x, figsize_y))
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.99       300
+           1       0.96      0.89      0.92       150
+           2       0.89      0.94      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Testing Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9516666666666667
+Testing Precision Score for RandomizedSearchRandomForestClassifier: 0.9516666666666667
+Testing Recall Score for RandomizedSearchRandomForestClassifier: 0.9516666666666667
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.90      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomizedSearchRandomForestClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.90      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 1 1 2 1 0 1 1 1 1 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 1 1 0 2 0 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+1    40
+0    37
+2    23
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifier.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifier_LabelsOnly.csv
+Models:  79%|███████▊  | 11/14 [06:25<02:32, 50.82s/it]RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 1800, 'min_samples_split': 2, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 60, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(max_depth=60, max_features='log2', min_samples_leaf=2,
+                       n_estimators=1800)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9609722222222222
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9990972222222222
+Validation Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9466666666666667
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.95      0.88      0.91       150
+           2       0.88      0.93      0.91       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9466666666666667
+Testing Precision Score for RandomizedSearchRandomForestClassifierV2: 0.9466666666666667
+Testing Recall Score for RandomizedSearchRandomForestClassifierV2: 0.9466666666666667
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.91      0.91       150
+           2       0.91      0.91      0.91       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomizedSearchRandomForestClassifierV2 in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.91      0.91       150
+           2       0.91      0.91      0.91       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 2 0 0 0 1 1 1 1 1 0 1 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
+ 0 2 1 1 0 1 0 2 2 2 1 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+0    44
+1    42
+2    14
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifierV2_Part_B_Result_Distribution.png
+Models:  86%|████████▌ | 12/14 [14:53<06:19, 189.97s/it]Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
+RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'uniform', 'p': 1, 'n_neighbors': 1}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(n_neighbors=1, p=1)
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.9634722222222222
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.945
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.96      0.87      0.92       150
+           2       0.86      0.95      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.94      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.94
+Testing Precision Score for RandomizedSearchKNeighborsClassifier: 0.94
+Testing Recall Score for RandomizedSearchKNeighborsClassifier: 0.94
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+Classification Report for RandomizedSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 0 1 2 2 2 1 2 2 0 2 2 2 2 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    42
+1    33
+2    25
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
+Models:  93%|█████████▎| 13/14 [15:01<02:14, 134.68s/it]GridSearchKNeighborsClassifier best parameters: 
+{'leaf_size': 20, 'metric': 'manhattan', 'n_neighbors': 1, 'weights': 'uniform'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(leaf_size=20, metric='manhattan', n_neighbors=1)
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.9634722222222222
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for GridSearchKNeighborsClassifier: 0.945
+Classification Report for GridSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.96      0.87      0.92       150
+           2       0.86      0.95      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.94      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchKNeighborsClassifier: 0.94
+Testing Precision Score for GridSearchKNeighborsClassifier: 0.94
+Testing Recall Score for GridSearchKNeighborsClassifier: 0.94
+Classification Report for GridSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+Classification Report for GridSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 0 1 2 2 2 1 2 2 0 2 2 2 2 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    42
+1    33
+2    25
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Models: 100%|██████████| 14/14 [15:47<00:00, 67.70s/it] 
+Saved Dataframe to: TestingResultsMulti_GridSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsMulti_GridSearchKNeighborsClassifier_LabelsOnly.csv
+Remember this is for PART: B
+
+Process finished with exit code 0
diff --git a/Program Outputs/Part_B_Output_Np_CV.txt b/Program Outputs/Part_B_Output_Np_CV.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7f1917870d4da3af28595db5e5a57d264d01ca48
--- /dev/null
+++ b/Program Outputs/Part_B_Output_Np_CV.txt	
@@ -0,0 +1,765 @@
+C:\Users\uwu\miniconda3\envs\comp3217\python.exe E:\Documents\Github\comp3217-2023-cw2\main.py
+Loading Config for TASK B
+Random Shuffle Seed: 42
+CV Folds: 10
+Test Ratio: 0.1
+Validation Ratio: 0.1
+Test Ratio: 0.8
+Using Validation Set
+SMOTE-ing Test Data
+Models:   0%|          | 0/14 [00:00<?, ?it/s]Evaluating ALL models: 
+LogisticRegression, LogisticRegressionliblinear, LinearSVC, KNeighbors, SVCrbf, SVCsigmoid, DecisionTreeClassifier, RandomForestClassifier, RandomizedSearchSVC, GridSearchSVC, RandomizedSearchRandomForestClassifier, RandomizedSearchRandomForestClassifierV2, RandomizedSearchKNeighborsClassifier, GridSearchKNeighborsClassifier
+Validation Accuracy Score for LogisticRegression: 0.7266666666666667
+Classification Report for LogisticRegression_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.86      0.90      0.88       300
+           1       0.61      0.55      0.58       150
+           2       0.56      0.56      0.56       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegression: 0.6716666666666666
+Testing Precision Score for LogisticRegression: 0.6716666666666666
+Testing Recall Score for LogisticRegression: 0.6716666666666666
+Classification Report for LogisticRegression_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.53      0.46      0.49       150
+           2       0.42      0.41      0.42       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.67      0.66       600
+
+Classification Report for LogisticRegression in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.53      0.46      0.49       150
+           2       0.42      0.41      0.42       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.67      0.66       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 0 1 1 0 2 1 2 2 2 1 0 2 1 1 1 1 2 1 1 1 2 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    44
+1    41
+2    15
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegression_Part_B_Result_Distribution.png
+Models:   7%|▋         | 1/14 [00:01<00:23,  1.80s/it]Saved Dataframe to: TestingResultsMulti_LogisticRegression.csv
+Saved Dataframe to: TestingResultsMulti_LogisticRegression_LabelsOnly.csv
+Validation Accuracy Score for LogisticRegressionliblinear: 0.7266666666666667
+Classification Report for LogisticRegressionliblinear_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.90      0.87       300
+           1       0.62      0.53      0.57       150
+           2       0.57      0.57      0.57       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LogisticRegressionliblinear: 0.6733333333333333
+Testing Precision Score for LogisticRegressionliblinear: 0.6733333333333333
+Testing Recall Score for LogisticRegressionliblinear: 0.6733333333333333
+Classification Report for LogisticRegressionliblinear_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.82      0.92      0.87       300
+           1       0.57      0.47      0.52       150
+           2       0.41      0.38      0.40       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.65      0.67      0.66       600
+
+Classification Report for LogisticRegressionliblinear in Part B:
+              precision    recall  f1-score   support
+
+           0       0.82      0.92      0.87       300
+           1       0.57      0.47      0.52       150
+           2       0.41      0.38      0.40       150
+
+    accuracy                           0.67       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.65      0.67      0.66       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 0 2 2 2 0 0 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 0 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0]
+0    44
+1    33
+2    23
+Name: Label, dtype: int64
+Saved distribution plot to: LogisticRegressionliblinear_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_LogisticRegressionliblinear.csv
+Saved Dataframe to: TestingResultsMulti_LogisticRegressionliblinear_LabelsOnly.csv
+Models:  14%|█▍        | 2/14 [00:05<00:37,  3.09s/it]C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+Validation Accuracy Score for LinearSVC: 0.7316666666666667
+Classification Report for LinearSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.87      0.92      0.89       300
+           1       0.60      0.53      0.57       150
+           2       0.56      0.56      0.56       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.73       600
+
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for LinearSVC: 0.675
+Testing Precision Score for LinearSVC: 0.675
+Testing Recall Score for LinearSVC: 0.675
+Classification Report for LinearSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.83      0.92      0.87       300
+           1       0.55      0.46      0.50       150
+           2       0.42      0.40      0.41       150
+
+    accuracy                           0.68       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.68      0.66       600
+
+Classification Report for LinearSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.83      0.92      0.87       300
+           1       0.55      0.46      0.50       150
+           2       0.42      0.40      0.41       150
+
+    accuracy                           0.68       600
+   macro avg       0.60      0.59      0.59       600
+weighted avg       0.66      0.68      0.66       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 0 0 0 1 1 1 1 1 2 2 2 2 2 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 0 2 0 0 2 1 0 0 0 0 0 1 1 1 1 1 2 1 1 1 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
+0    55
+1    34
+2    11
+Name: Label, dtype: int64
+Saved distribution plot to: LinearSVC_Part_B_Result_Distribution.png
+Models:  21%|██▏       | 3/14 [02:12<10:56, 59.68s/it]Saved Dataframe to: TestingResultsMulti_LinearSVC.csv
+Saved Dataframe to: TestingResultsMulti_LinearSVC_LabelsOnly.csv
+Validation Accuracy Score for KNeighbors: 0.8683333333333333
+Classification Report for KNeighbors_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.92      0.94      0.93       300
+           1       0.89      0.77      0.82       150
+           2       0.75      0.83      0.79       150
+
+    accuracy                           0.87       600
+   macro avg       0.85      0.85      0.85       600
+weighted avg       0.87      0.87      0.87       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for KNeighbors: 0.8833333333333333
+Testing Precision Score for KNeighbors: 0.8833333333333333
+Testing Recall Score for KNeighbors: 0.8833333333333333
+Classification Report for KNeighbors_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.84      0.80      0.82       150
+           2       0.79      0.85      0.82       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.89      0.88      0.88       600
+
+Classification Report for KNeighbors in Part B:
+              precision    recall  f1-score   support
+
+           0       0.96      0.94      0.95       300
+           1       0.84      0.80      0.82       150
+           2       0.79      0.85      0.82       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.89      0.88      0.88       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 2 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1
+ 1 1 0 0 0 1 1 2 0 0 1 2 1 0 2 2 2 2 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 0 1 1 1 1 1 2 2 0 1 1 1 1 0 0 0 0]
+0    42
+1    38
+2    20
+Name: Label, dtype: int64
+Saved distribution plot to: KNeighbors_Part_B_Result_Distribution.png
+Models:  29%|██▊       | 4/14 [02:13<06:05, 36.55s/it]Saved Dataframe to: TestingResultsMulti_KNeighbors.csv
+Saved Dataframe to: TestingResultsMulti_KNeighbors_LabelsOnly.csv
+Validation Accuracy Score for SVCrbf: 0.7583333333333333
+Classification Report for SVCrbf_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.86      0.90      0.88       300
+           1       0.68      0.61      0.64       150
+           2       0.61      0.62      0.62       150
+
+    accuracy                           0.76       600
+   macro avg       0.72      0.71      0.71       600
+weighted avg       0.75      0.76      0.76       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for SVCrbf: 0.7283333333333334
+Testing Precision Score for SVCrbf: 0.7283333333333334
+Testing Recall Score for SVCrbf: 0.7283333333333334
+Classification Report for SVCrbf_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.67      0.57      0.62       150
+           2       0.53      0.51      0.52       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+Classification Report for SVCrbf in Part B:
+              precision    recall  f1-score   support
+
+           0       0.84      0.91      0.87       300
+           1       0.67      0.57      0.62       150
+           2       0.53      0.51      0.52       150
+
+    accuracy                           0.73       600
+   macro avg       0.68      0.67      0.67       600
+weighted avg       0.72      0.73      0.72       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 2 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1
+ 1 2 1 1 0 2 0 2 2 2 1 0 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0]
+1    39
+0    37
+2    24
+Name: Label, dtype: int64
+Saved distribution plot to: SVCrbf_Part_B_Result_Distribution.png
+Models:  36%|███▌      | 5/14 [02:30<04:23, 29.23s/it]Saved Dataframe to: TestingResultsMulti_SVCrbf.csv
+Saved Dataframe to: TestingResultsMulti_SVCrbf_LabelsOnly.csv
+Validation Accuracy Score for SVCsigmoid: 0.49333333333333335
+Classification Report for SVCsigmoid_Against_Validation_Set in Part B:
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+              precision    recall  f1-score   support
+
+           0       0.80      0.53      0.64       300
+           1       0.34      0.52      0.41       150
+           2       0.34      0.39      0.36       150
+
+    accuracy                           0.49       600
+   macro avg       0.49      0.48      0.47       600
+weighted avg       0.57      0.49      0.51       600
+
+Testing Accuracy Score for SVCsigmoid: 0.48333333333333334
+Testing Precision Score for SVCsigmoid: 0.48333333333333334
+Testing Recall Score for SVCsigmoid: 0.48333333333333334
+Classification Report for SVCsigmoid_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.80      0.55      0.65       300
+           1       0.33      0.51      0.40       150
+           2       0.30      0.32      0.31       150
+
+    accuracy                           0.48       600
+   macro avg       0.48      0.46      0.45       600
+weighted avg       0.56      0.48      0.50       600
+
+Classification Report for SVCsigmoid in Part B:
+              precision    recall  f1-score   support
+
+           0       0.80      0.55      0.65       300
+           1       0.33      0.51      0.40       150
+           2       0.30      0.32      0.31       150
+
+    accuracy                           0.48       600
+   macro avg       0.48      0.46      0.45       600
+weighted avg       0.56      0.48      0.50       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 2 2 2 2 2 1 1 1 1 1 2 2 2 2 2 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 2 0 0 2 0 1 1 1 2 0 1 1 1 1 1 0 2 2 2 1 2 1 2 2 2 2 2 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 2 0 2 1 2 2 2 2 2 0 1 1 1 1 1 1 1 1]
+1    46
+2    30
+0    24
+Name: Label, dtype: int64
+Saved distribution plot to: SVCsigmoid_Part_B_Result_Distribution.png
+Models:  43%|████▎     | 6/14 [02:42<03:08, 23.61s/it]Saved Dataframe to: TestingResultsMulti_SVCsigmoid.csv
+Saved Dataframe to: TestingResultsMulti_SVCsigmoid_LabelsOnly.csv
+Validation Accuracy Score for DecisionTreeClassifier: 0.8633333333333333
+Classification Report for DecisionTreeClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.91      0.94      0.92       300
+           1       0.86      0.80      0.83       150
+           2       0.77      0.78      0.78       150
+
+    accuracy                           0.86       600
+   macro avg       0.85      0.84      0.84       600
+weighted avg       0.86      0.86      0.86       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for DecisionTreeClassifier: 0.8816666666666667
+Testing Precision Score for DecisionTreeClassifier: 0.8816666666666667
+Testing Recall Score for DecisionTreeClassifier: 0.8816666666666667
+Classification Report for DecisionTreeClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.93      0.95      0.94       300
+           1       0.86      0.83      0.84       150
+           2       0.80      0.79      0.80       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.88      0.88      0.88       600
+
+Classification Report for DecisionTreeClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.93      0.95      0.94       300
+           1       0.86      0.83      0.84       150
+           2       0.80      0.79      0.80       150
+
+    accuracy                           0.88       600
+   macro avg       0.86      0.86      0.86       600
+weighted avg       0.88      0.88      0.88       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 2 2 2 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 0 0 1 2 2 2 2 1 0 2 2 2 2 2 2 2 0 0 2 2 2 2 2 2 2 1 1 1 0 0 1 1 1
+ 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1]
+1    63
+2    24
+0    13
+Name: Label, dtype: int64
+Saved distribution plot to: DecisionTreeClassifier_Part_B_Result_Distribution.png
+Models:  50%|█████     | 7/14 [02:44<01:54, 16.32s/it]Saved Dataframe to: TestingResultsMulti_DecisionTreeClassifier.csv
+Saved Dataframe to: TestingResultsMulti_DecisionTreeClassifier_LabelsOnly.csv
+Validation Accuracy Score for RandomForestClassifier: 0.96
+Classification Report for RandomForestClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.99      0.99      0.99       300
+           1       0.97      0.91      0.94       150
+           2       0.90      0.95      0.93       150
+
+    accuracy                           0.96       600
+   macro avg       0.95      0.95      0.95       600
+weighted avg       0.96      0.96      0.96       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomForestClassifier: 0.9516666666666667
+Testing Precision Score for RandomForestClassifier: 0.9516666666666667
+Testing Recall Score for RandomForestClassifier: 0.9516666666666667
+Classification Report for RandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.90      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomForestClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.90      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 2 2 2 1 0 0 0 0 0 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 1 1 0 1 1 2 2 2 1 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+0    40
+1    38
+2    22
+Name: Label, dtype: int64
+Saved distribution plot to: RandomForestClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomForestClassifier.csv
+Models:  57%|█████▋    | 8/14 [03:21<02:17, 22.96s/it]Saved Dataframe to: TestingResultsMulti_RandomForestClassifier_LabelsOnly.csv
+RandomizedSearchSVC best parameters: 
+{'kernel': 'rbf', 'gamma': 1, 'C': 1}
+RandomizedSearchSVC best estimator: 
+SVC(C=1, gamma=1, probability=True)
+CV Mean Test Accuracy for RandomizedSearchSVC best estimator: 0.8963888888888888
+CV Mean Train Accuracy for RandomizedSearchSVC best estimator: 0.9787499999999999
+Validation Accuracy Score for RandomizedSearchSVC: 0.8416666666666667
+Classification Report for RandomizedSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.94      0.88      0.91       300
+           1       0.70      0.87      0.78       150
+           2       0.83      0.73      0.78       150
+
+    accuracy                           0.84       600
+   macro avg       0.82      0.83      0.82       600
+weighted avg       0.85      0.84      0.84       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchSVC: 0.8616666666666667
+Testing Precision Score for RandomizedSearchSVC: 0.8616666666666667
+Testing Recall Score for RandomizedSearchSVC: 0.8616666666666667
+Classification Report for RandomizedSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.89      0.93       300
+           1       0.69      0.92      0.79       150
+           2       0.90      0.74      0.81       150
+
+    accuracy                           0.86       600
+   macro avg       0.85      0.85      0.84       600
+weighted avg       0.88      0.86      0.87       600
+
+Classification Report for RandomizedSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.89      0.93       300
+           1       0.69      0.92      0.79       150
+           2       0.90      0.74      0.81       150
+
+    accuracy                           0.86       600
+   macro avg       0.85      0.85      0.84       600
+weighted avg       0.88      0.86      0.87       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
+1    100
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchSVC_Part_B_Result_Distribution.png
+Models:  64%|██████▍   | 9/14 [04:14<02:42, 32.43s/it]Saved Dataframe to: TestingResultsMulti_RandomizedSearchSVC.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchSVC_LabelsOnly.csv
+GridSearchSVC best parameters: 
+{'C': 100, 'gamma': 0.1, 'kernel': 'rbf'}
+GridSearchSVC best estimator: 
+SVC(C=100, gamma=0.1, probability=True)
+CV Mean Test Accuracy for GridSearchSVC best estimator: 0.9301388888888887
+CV Mean Train Accuracy for GridSearchSVC best estimator: 0.991111111111111
+Validation Accuracy Score for GridSearchSVC: 0.895
+Classification Report for GridSearchSVC_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.95      0.94      0.94       300
+           1       0.86      0.87      0.86       150
+           2       0.83      0.83      0.83       150
+
+    accuracy                           0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchSVC: 0.9166666666666666
+Testing Precision Score for GridSearchSVC: 0.9166666666666666
+Testing Recall Score for GridSearchSVC: 0.9166666666666666
+Classification Report for GridSearchSVC_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+Classification Report for GridSearchSVC in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.95      0.96       300
+           1       0.84      0.94      0.89       150
+           2       0.91      0.83      0.87       150
+
+    accuracy                           0.92       600
+   macro avg       0.90      0.91      0.90       600
+weighted avg       0.92      0.92      0.92       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [2 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1
+ 1 1 1 1 0 1 1 1 0 0 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0
+ 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 0 1 1 0 0 0 0 0 0]
+1    48
+0    40
+2    12
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchSVC_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_GridSearchSVC.csv
+Saved Dataframe to: TestingResultsMulti_GridSearchSVC_LabelsOnly.csv
+Models:  71%|███████▏  | 10/14 [05:21<02:52, 43.08s/it]RandomizedSearchRandomForestClassifier best parameters: 
+{'n_estimators': 1200, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_depth': 70, 'bootstrap': True}
+RandomizedSearchRandomForestClassifier best estimator: 
+RandomForestClassifier(max_depth=70, n_estimators=1200)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifier best estimator: 0.9645833333333332
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifier: 0.95
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.99       300
+           1       0.95      0.89      0.92       150
+           2       0.89      0.93      0.91       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+E:\Documents\Github\comp3217-2023-cw2\utils.py:264: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
+  fig, ax = plt.subplots(figsize=(figsize_x, figsize_y))
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifier: 0.9483333333333334
+Testing Precision Score for RandomizedSearchRandomForestClassifier: 0.9483333333333334
+Testing Recall Score for RandomizedSearchRandomForestClassifier: 0.9483333333333334
+Classification Report for RandomizedSearchRandomForestClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.99      0.98       300
+           1       0.93      0.90      0.92       150
+           2       0.91      0.92      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomizedSearchRandomForestClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.97      0.99      0.98       300
+           1       0.93      0.90      0.92       150
+           2       0.91      0.92      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 2 2 2 2
+ 2 2 1 1 0 1 1 2 2 2 1 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+1    44
+0    36
+2    20
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifier_Part_B_Result_Distribution.png
+Models:  79%|███████▊  | 11/14 [06:46<02:47, 55.84s/it]Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifier.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifier_LabelsOnly.csv
+RandomizedSearchRandomForestClassifierV2 best parameters: 
+{'n_estimators': 1800, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_features': 'log2', 'max_depth': 60, 'bootstrap': True}
+RandomizedSearchRandomForestClassifierV2 best estimator: 
+RandomForestClassifier(max_depth=60, max_features='log2', n_estimators=1800)
+CV Mean Test Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 0.9658333333333333
+CV Mean Train Accuracy for RandomizedSearchRandomForestClassifierV2 best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.955
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.99       300
+           1       0.96      0.90      0.93       150
+           2       0.90      0.94      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.95      0.94      0.94       600
+weighted avg       0.96      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchRandomForestClassifierV2: 0.9533333333333334
+Testing Precision Score for RandomizedSearchRandomForestClassifierV2: 0.9533333333333334
+Testing Recall Score for RandomizedSearchRandomForestClassifierV2: 0.9533333333333334
+Classification Report for RandomizedSearchRandomForestClassifierV2_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.91      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+Classification Report for RandomizedSearchRandomForestClassifierV2 in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.99      0.98       300
+           1       0.94      0.91      0.92       150
+           2       0.92      0.93      0.92       150
+
+    accuracy                           0.95       600
+   macro avg       0.94      0.94      0.94       600
+weighted avg       0.95      0.95      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 1 1 1 1 1 2 2 2 0 0 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
+ 0 2 1 1 0 1 0 2 2 2 1 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0]
+0    44
+1    43
+2    13
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchRandomForestClassifierV2_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
+Models:  86%|████████▌ | 12/14 [14:30<06:00, 180.14s/it]RandomizedSearchKNeighborsClassifier best parameters: 
+{'weights': 'distance', 'p': 1, 'n_neighbors': 3}
+RandomizedSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(n_neighbors=3, p=1, weights='distance')
+CV Mean Test Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 0.9526388888888889
+CV Mean Train Accuracy for RandomizedSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.935
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.97      0.98       300
+           1       0.94      0.85      0.90       150
+           2       0.84      0.94      0.89       150
+
+    accuracy                           0.94       600
+   macro avg       0.92      0.92      0.92       600
+weighted avg       0.94      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for RandomizedSearchKNeighborsClassifier: 0.9366666666666666
+Testing Precision Score for RandomizedSearchKNeighborsClassifier: 0.9366666666666666
+Testing Recall Score for RandomizedSearchKNeighborsClassifier: 0.9366666666666666
+Classification Report for RandomizedSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.90      0.89      0.89       150
+           2       0.89      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.92      0.92      0.92       600
+weighted avg       0.94      0.94      0.94       600
+
+Classification Report for RandomizedSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.90      0.89      0.89       150
+           2       0.89      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.92      0.92      0.92       600
+weighted avg       0.94      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 1 1 2 2 2 1 2 2 0 2 2 2 2 1 1 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    42
+1    29
+2    29
+Name: Label, dtype: int64
+Saved distribution plot to: RandomizedSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsMulti_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
+Models:  93%|█████████▎| 13/14 [14:38<02:08, 128.01s/it]GridSearchKNeighborsClassifier best parameters: 
+{'leaf_size': 20, 'metric': 'manhattan', 'n_neighbors': 1, 'weights': 'uniform'}
+GridSearchKNeighborsClassifier best estimator: 
+KNeighborsClassifier(leaf_size=20, metric='manhattan', n_neighbors=1)
+CV Mean Test Accuracy for GridSearchKNeighborsClassifier best estimator: 0.9634722222222222
+CV Mean Train Accuracy for GridSearchKNeighborsClassifier best estimator: 1.0
+Validation Accuracy Score for GridSearchKNeighborsClassifier: 0.945
+Classification Report for GridSearchKNeighborsClassifier_Against_Validation_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.96      0.87      0.92       150
+           2       0.86      0.95      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.94      0.93      0.93       600
+weighted avg       0.95      0.94      0.95       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Testing Accuracy Score for GridSearchKNeighborsClassifier: 0.94
+Testing Precision Score for GridSearchKNeighborsClassifier: 0.94
+Testing Recall Score for GridSearchKNeighborsClassifier: 0.94
+Classification Report for GridSearchKNeighborsClassifier_Against_Test_Set in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+Classification Report for GridSearchKNeighborsClassifier in Part B:
+              precision    recall  f1-score   support
+
+           0       0.98      0.98      0.98       300
+           1       0.91      0.89      0.90       150
+           2       0.90      0.91      0.90       150
+
+    accuracy                           0.94       600
+   macro avg       0.93      0.93      0.93       600
+weighted avg       0.94      0.94      0.94       600
+
+C:\Users\uwu\miniconda3\envs\comp3217\lib\site-packages\sklearn\utils\deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.
+  warnings.warn(msg, category=FutureWarning)
+Final Predictions: [1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2
+ 2 2 0 0 0 0 1 2 2 2 1 2 2 0 2 2 2 2 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
+ 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0]
+0    42
+1    33
+2    25
+Name: Label, dtype: int64
+Saved distribution plot to: GridSearchKNeighborsClassifier_Part_B_Result_Distribution.png
+Models: 100%|██████████| 14/14 [15:23<00:00, 65.98s/it] 
+Saved Dataframe to: TestingResultsMulti_GridSearchKNeighborsClassifier.csv
+Saved Dataframe to: TestingResultsMulti_GridSearchKNeighborsClassifier_LabelsOnly.csv
+Remember this is for PART: B
+
+Process finished with exit code 0
diff --git a/TestingResultsMulti.csv b/TestingResultsMulti.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1bc714429eecdee1b733449597dc8656b9cc0105
--- /dev/null
+++ b/TestingResultsMulti.csv
@@ -0,0 +1,100 @@
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diff --git a/TestingResultsMulti_LabelsOnly.csv b/TestingResultsMulti_LabelsOnly.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2802f4f12913991a9d40e3c9bde949170b7b36c
--- /dev/null
+++ b/TestingResultsMulti_LabelsOnly.csv
@@ -0,0 +1,100 @@
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diff --git a/part_a_DEPRECATED.py b/part_a_DEPRECATED.py
index db1f43caa5612c811460f462a99f29f42cf07994..d0acdb575f0436f9b446b932cedfa1bcb231eee4 100644
--- a/part_a_DEPRECATED.py
+++ b/part_a_DEPRECATED.py
@@ -151,7 +151,7 @@ if __name__ == "__main__":
 
                 if SAVE_FINAL_ANSWER:
                     # Load test dataset
-                    final_answer_dataset = load_dataframe_from_csv(FINAL_ANSWER_DATASET_FILENAME, add_label=False)
+                    final_answer_dataset = load_dataframe_from_csv(FINAL_ANSWER_DATASET_FILENAME, has_label_column=False)
                     # Preprocess features using same values as when training
                     if PREPROCESS_DATASET:
                         final_answer_dataset = preprocess_dataset(drop_control_panel_logs=DROP_CONTROL_PANEL_LOGS,