From 750d82ff4f3012d50b3b50adc05765722219a94d Mon Sep 17 00:00:00 2001
From: Ethan Aherne <eca1g19@soton.ac.uk>
Date: Thu, 8 Jun 2023 11:55:18 +0100
Subject: [PATCH] Added All output files
---
Answers/TestingDataBinary.csv | 100 +++
Answers/TestingDataMulti.csv | 100 +++
Answers/TestingResultsBinary.csv | 100 +++
Answers/TestingResultsBinary_LabelsOnly.csv | 100 +++
Answers/TestingResultsMulti.csv | 100 +++
Answers/TestingResultsMulti_LabelsOnly.csv | 100 +++
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 37200 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 38230 bytes
...restClassifier_Part_A_Confusion_Matrix.png | Bin 0 -> 33082 bytes
...tClassifier_Part_A_Result_Distribution.png | Bin 0 -> 29892 bytes
...restClassifier_Part_B_Confusion_Matrix.png | Bin 0 -> 34719 bytes
...tClassifier_Part_B_Result_Distribution.png | Bin 0 -> 30112 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 38539 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 40912 bytes
...borsClassifier_Part_A_Confusion_Matrix.png | Bin 0 -> 35938 bytes
...sClassifier_Part_A_Result_Distribution.png | Bin 0 -> 30926 bytes
...borsClassifier_Part_B_Confusion_Matrix.png | Bin 0 -> 37906 bytes
...sClassifier_Part_B_Result_Distribution.png | Bin 0 -> 32374 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 40329 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 40579 bytes
...stClassifierV2_Part_A_Confusion_Matrix.png | Bin 0 -> 36281 bytes
...lassifierV2_Part_A_Result_Distribution.png | Bin 0 -> 32219 bytes
...stClassifierV2_Part_B_Confusion_Matrix.png | Bin 0 -> 38124 bytes
...lassifierV2_Part_B_Result_Distribution.png | Bin 0 -> 30044 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 39846 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 40525 bytes
...restClassifier_Part_A_Confusion_Matrix.png | Bin 0 -> 35820 bytes
...tClassifier_Part_A_Result_Distribution.png | Bin 0 -> 31045 bytes
...restClassifier_Part_B_Confusion_Matrix.png | Bin 0 -> 37607 bytes
...tClassifier_Part_B_Result_Distribution.png | Bin 0 -> 29495 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 37171 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 39672 bytes
...mizedSearchSVC_Part_A_Confusion_Matrix.png | Bin 0 -> 33593 bytes
...edSearchSVC_Part_A_Result_Distribution.png | Bin 0 -> 29184 bytes
...mizedSearchSVC_Part_B_Confusion_Matrix.png | Bin 0 -> 36137 bytes
...edSearchSVC_Part_B_Result_Distribution.png | Bin 0 -> 29120 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 34700 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 37508 bytes
Images/SVCrbf_Part_A_Confusion_Matrix.png | Bin 0 -> 31677 bytes
Images/SVCrbf_Part_A_Result_Distribution.png | Bin 0 -> 27537 bytes
Images/SVCrbf_Part_B_Confusion_Matrix.png | Bin 0 -> 33756 bytes
Images/SVCrbf_Part_B_Result_Distribution.png | Bin 0 -> 28977 bytes
...Validation_Set_Part_A_Confusion_Matrix.png | Bin 0 -> 38262 bytes
...Validation_Set_Part_B_Confusion_Matrix.png | Bin 0 -> 40517 bytes
Images/SVCsigmoid_Part_A_Confusion_Matrix.png | Bin 0 -> 33679 bytes
.../SVCsigmoid_Part_A_Result_Distribution.png | Bin 0 -> 29351 bytes
Images/SVCsigmoid_Part_B_Confusion_Matrix.png | Bin 0 -> 36791 bytes
.../SVCsigmoid_Part_B_Result_Distribution.png | Bin 0 -> 27842 bytes
...ngResultsBinary_DecisionTreeClassifier.csv | 100 +++
...nary_DecisionTreeClassifier_LabelsOnly.csv | 100 +++
...sBinary_GridSearchKNeighborsClassifier.csv | 100 +++
...dSearchKNeighborsClassifier_LabelsOnly.csv | 100 +++
.../TestingResultsBinary_GridSearchSVC.csv | 100 +++
...ResultsBinary_GridSearchSVC_LabelsOnly.csv | 100 +++
.../TestingResultsBinary_KNeighbors.csv | 100 +++
...ingResultsBinary_KNeighbors_LabelsOnly.csv | 100 +++
.../TestingResultsBinary_LabelsOnly.csv | 0
.../TestingResultsBinary_LinearSVC.csv | 100 +++
...tingResultsBinary_LinearSVC_LabelsOnly.csv | 100 +++
...estingResultsBinary_LogisticRegression.csv | 100 +++
...tsBinary_LogisticRegression_LabelsOnly.csv | 100 +++
...ultsBinary_LogisticRegressionliblinear.csv | 100 +++
...LogisticRegressionliblinear_LabelsOnly.csv | 100 +++
...ngResultsBinary_RandomForestClassifier.csv | 100 +++
...nary_RandomForestClassifier_LabelsOnly.csv | 100 +++
...y_RandomizedSearchKNeighborsClassifier.csv | 100 +++
...dSearchKNeighborsClassifier_LabelsOnly.csv | 100 +++
...RandomizedSearchRandomForestClassifier.csv | 80 +-
...ndomizedSearchRandomForestClassifierV2.csv | 92 +--
...rchRandomForestClassifierV2_LabelsOnly.csv | 100 +++
...earchRandomForestClassifier_LabelsOnly.csv | 60 +-
...stingResultsBinary_RandomizedSearchSVC.csv | 100 +++
...sBinary_RandomizedSearchSVC_LabelsOnly.csv | 100 +++
Model Results/TestingResultsBinary_SVCrbf.csv | 100 +++
...TestingResultsBinary_SVCrbf_LabelsOnly.csv | 100 +++
.../TestingResultsBinary_SVCsigmoid.csv | 100 +++
...ingResultsBinary_SVCsigmoid_LabelsOnly.csv | 100 +++
...ingResultsMulti_DecisionTreeClassifier.csv | 100 +++
...ulti_DecisionTreeClassifier_LabelsOnly.csv | 100 +++
...tsMulti_GridSearchKNeighborsClassifier.csv | 100 +++
...dSearchKNeighborsClassifier_LabelsOnly.csv | 100 +++
.../TestingResultsMulti_GridSearchSVC.csv | 100 +++
...gResultsMulti_GridSearchSVC_LabelsOnly.csv | 100 +++
.../TestingResultsMulti_KNeighbors.csv | 100 +++
...tingResultsMulti_KNeighbors_LabelsOnly.csv | 100 +++
.../TestingResultsMulti_LinearSVC.csv | 100 +++
...stingResultsMulti_LinearSVC_LabelsOnly.csv | 100 +++
...TestingResultsMulti_LogisticRegression.csv | 100 +++
...ltsMulti_LogisticRegression_LabelsOnly.csv | 100 +++
...sultsMulti_LogisticRegressionliblinear.csv | 100 +++
...LogisticRegressionliblinear_LabelsOnly.csv | 100 +++
...ingResultsMulti_RandomForestClassifier.csv | 100 +++
...ulti_RandomForestClassifier_LabelsOnly.csv | 100 +++
...i_RandomizedSearchKNeighborsClassifier.csv | 100 +++
...dSearchKNeighborsClassifier_LabelsOnly.csv | 100 +++
...RandomizedSearchRandomForestClassifier.csv | 100 +++
...ndomizedSearchRandomForestClassifierV2.csv | 100 +++
...rchRandomForestClassifierV2_LabelsOnly.csv | 100 +++
...earchRandomForestClassifier_LabelsOnly.csv | 100 +++
...estingResultsMulti_RandomizedSearchSVC.csv | 100 +++
...tsMulti_RandomizedSearchSVC_LabelsOnly.csv | 100 +++
Model Results/TestingResultsMulti_SVCrbf.csv | 100 +++
.../TestingResultsMulti_SVCrbf_LabelsOnly.csv | 100 +++
.../TestingResultsMulti_SVCsigmoid.csv | 100 +++
...tingResultsMulti_SVCsigmoid_LabelsOnly.csv | 100 +++
.../TrainingDataBinary.csv | 0
.../TrainingDataBinaryWithHeaders.csv | 0
Program Outputs/Part_A_Output_CV.txt | 132 +++
Program Outputs/Part_A_Output_No_CV.txt | 552 +++++++++++++
Program Outputs/Part_A_Output_No_CV_2.txt | 710 ++++++++++++++++
Program Outputs/Part_B_Output_No_CV.txt | 769 ++++++++++++++++++
Program Outputs/Part_B_Output_No_CV2.txt | 768 +++++++++++++++++
Program Outputs/Part_B_Output_Np_CV.txt | 765 +++++++++++++++++
TestingResultsMulti.csv | 100 +++
TestingResultsMulti_LabelsOnly.csv | 100 +++
part_a_DEPRECATED.py | 2 +-
116 files changed, 9913 insertions(+), 117 deletions(-)
create mode 100644 Answers/TestingDataBinary.csv
create mode 100644 Answers/TestingDataMulti.csv
create mode 100644 Answers/TestingResultsBinary.csv
create mode 100644 Answers/TestingResultsBinary_LabelsOnly.csv
create mode 100644 Answers/TestingResultsMulti.csv
create mode 100644 Answers/TestingResultsMulti_LabelsOnly.csv
create mode 100644 Images/RandomForestClassifier_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomForestClassifier_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomForestClassifier_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomForestClassifier_Part_A_Result_Distribution.png
create mode 100644 Images/RandomForestClassifier_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomForestClassifier_Part_B_Result_Distribution.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Part_A_Result_Distribution.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchKNeighborsClassifier_Part_B_Result_Distribution.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Part_A_Result_Distribution.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifierV2_Part_B_Result_Distribution.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Part_A_Result_Distribution.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchRandomForestClassifier_Part_B_Result_Distribution.png
create mode 100644 Images/RandomizedSearchSVC_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchSVC_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchSVC_Part_A_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchSVC_Part_A_Result_Distribution.png
create mode 100644 Images/RandomizedSearchSVC_Part_B_Confusion_Matrix.png
create mode 100644 Images/RandomizedSearchSVC_Part_B_Result_Distribution.png
create mode 100644 Images/SVCrbf_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/SVCrbf_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/SVCrbf_Part_A_Confusion_Matrix.png
create mode 100644 Images/SVCrbf_Part_A_Result_Distribution.png
create mode 100644 Images/SVCrbf_Part_B_Confusion_Matrix.png
create mode 100644 Images/SVCrbf_Part_B_Result_Distribution.png
create mode 100644 Images/SVCsigmoid_Against_Validation_Set_Part_A_Confusion_Matrix.png
create mode 100644 Images/SVCsigmoid_Against_Validation_Set_Part_B_Confusion_Matrix.png
create mode 100644 Images/SVCsigmoid_Part_A_Confusion_Matrix.png
create mode 100644 Images/SVCsigmoid_Part_A_Result_Distribution.png
create mode 100644 Images/SVCsigmoid_Part_B_Confusion_Matrix.png
create mode 100644 Images/SVCsigmoid_Part_B_Result_Distribution.png
create mode 100644 Model Results/TestingResultsBinary_DecisionTreeClassifier.csv
create mode 100644 Model Results/TestingResultsBinary_DecisionTreeClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv
create mode 100644 Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_GridSearchSVC.csv
create mode 100644 Model Results/TestingResultsBinary_GridSearchSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_KNeighbors.csv
create mode 100644 Model Results/TestingResultsBinary_KNeighbors_LabelsOnly.csv
rename TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv => Model Results/TestingResultsBinary_LabelsOnly.csv (100%)
create mode 100644 Model Results/TestingResultsBinary_LinearSVC.csv
create mode 100644 Model Results/TestingResultsBinary_LinearSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_LogisticRegression.csv
create mode 100644 Model Results/TestingResultsBinary_LogisticRegression_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_LogisticRegressionliblinear.csv
create mode 100644 Model Results/TestingResultsBinary_LogisticRegressionliblinear_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_RandomForestClassifier.csv
create mode 100644 Model Results/TestingResultsBinary_RandomForestClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_RandomizedSearchKNeighborsClassifier.csv
create mode 100644 Model Results/TestingResultsBinary_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
rename TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv => Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv (98%)
rename TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv => Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2.csv (98%)
create mode 100644 Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
rename TestingResultsBinary_RandomizedSearchRandomForestClassifier_LabelsOnly.csv => Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier_LabelsOnly.csv (86%)
create mode 100644 Model Results/TestingResultsBinary_RandomizedSearchSVC.csv
create mode 100644 Model Results/TestingResultsBinary_RandomizedSearchSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_SVCrbf.csv
create mode 100644 Model Results/TestingResultsBinary_SVCrbf_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsBinary_SVCsigmoid.csv
create mode 100644 Model Results/TestingResultsBinary_SVCsigmoid_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_DecisionTreeClassifier.csv
create mode 100644 Model Results/TestingResultsMulti_DecisionTreeClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier.csv
create mode 100644 Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_GridSearchSVC.csv
create mode 100644 Model Results/TestingResultsMulti_GridSearchSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_KNeighbors.csv
create mode 100644 Model Results/TestingResultsMulti_KNeighbors_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_LinearSVC.csv
create mode 100644 Model Results/TestingResultsMulti_LinearSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_LogisticRegression.csv
create mode 100644 Model Results/TestingResultsMulti_LogisticRegression_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_LogisticRegressionliblinear.csv
create mode 100644 Model Results/TestingResultsMulti_LogisticRegressionliblinear_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_RandomForestClassifier.csv
create mode 100644 Model Results/TestingResultsMulti_RandomForestClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchKNeighborsClassifier.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchKNeighborsClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifier.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifierV2.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchRandomForestClassifier_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchSVC.csv
create mode 100644 Model Results/TestingResultsMulti_RandomizedSearchSVC_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_SVCrbf.csv
create mode 100644 Model Results/TestingResultsMulti_SVCrbf_LabelsOnly.csv
create mode 100644 Model Results/TestingResultsMulti_SVCsigmoid.csv
create mode 100644 Model Results/TestingResultsMulti_SVCsigmoid_LabelsOnly.csv
rename TrainingDataBinary.csv => Model Results/TrainingDataBinary.csv (100%)
rename TrainingDataBinaryWithHeaders.csv => Model Results/TrainingDataBinaryWithHeaders.csv (100%)
create mode 100644 Program Outputs/Part_A_Output_CV.txt
create mode 100644 Program Outputs/Part_A_Output_No_CV.txt
create mode 100644 Program Outputs/Part_A_Output_No_CV_2.txt
create mode 100644 Program Outputs/Part_B_Output_No_CV.txt
create mode 100644 Program Outputs/Part_B_Output_No_CV2.txt
create mode 100644 Program Outputs/Part_B_Output_Np_CV.txt
create mode 100644 TestingResultsMulti.csv
create mode 100644 TestingResultsMulti_LabelsOnly.csv
diff --git a/Answers/TestingDataBinary.csv b/Answers/TestingDataBinary.csv
new file mode 100644
index 0000000..0af9dd4
--- /dev/null
+++ b/Answers/TestingDataBinary.csv
@@ -0,0 +1,100 @@
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diff --git a/Answers/TestingDataMulti.csv b/Answers/TestingDataMulti.csv
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index 0000000..54853db
--- /dev/null
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diff --git a/Answers/TestingResultsBinary.csv b/Answers/TestingResultsBinary.csv
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diff --git a/Answers/TestingResultsMulti.csv b/Answers/TestingResultsMulti.csv
new file mode 100644
index 0000000..1bc7144
--- /dev/null
+++ b/Answers/TestingResultsMulti.csv
@@ -0,0 +1,100 @@
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diff --git a/Answers/TestingResultsMulti_LabelsOnly.csv b/Answers/TestingResultsMulti_LabelsOnly.csv
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diff --git a/Model Results/TestingResultsBinary_DecisionTreeClassifier.csv b/Model Results/TestingResultsBinary_DecisionTreeClassifier.csv
new file mode 100644
index 0000000..6312e00
--- /dev/null
+++ b/Model Results/TestingResultsBinary_DecisionTreeClassifier.csv
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diff --git a/Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv b/Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv
new file mode 100644
index 0000000..cfdfe24
--- /dev/null
+++ b/Model Results/TestingResultsBinary_GridSearchKNeighborsClassifier.csv
@@ -0,0 +1,100 @@
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diff --git a/Model Results/TestingResultsBinary_GridSearchSVC.csv b/Model Results/TestingResultsBinary_GridSearchSVC.csv
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diff --git a/Model Results/TestingResultsBinary_KNeighbors.csv b/Model Results/TestingResultsBinary_KNeighbors.csv
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diff --git a/Model Results/TestingResultsBinary_KNeighbors_LabelsOnly.csv b/Model Results/TestingResultsBinary_KNeighbors_LabelsOnly.csv
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diff --git a/TestingResultsBinary_RandomizedSearchRandomForestClassifierV2_LabelsOnly.csv b/Model Results/TestingResultsBinary_LabelsOnly.csv
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diff --git a/Model Results/TestingResultsBinary_LogisticRegressionliblinear.csv b/Model Results/TestingResultsBinary_LogisticRegressionliblinear.csv
new file mode 100644
index 0000000..20a645c
--- /dev/null
+++ b/Model Results/TestingResultsBinary_LogisticRegressionliblinear.csv
@@ -0,0 +1,100 @@
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diff --git a/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv b/Model Results/TestingResultsBinary_RandomizedSearchRandomForestClassifier.csv
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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 2ffc6db..0c431a4 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 0000000..53f35a1
--- /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 0000000..fbec2fb
--- /dev/null
+++ b/Model Results/TestingResultsMulti_GridSearchKNeighborsClassifier.csv
@@ -0,0 +1,100 @@
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diff --git a/Model Results/TestingResultsMulti_GridSearchSVC.csv b/Model Results/TestingResultsMulti_GridSearchSVC.csv
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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_LogisticRegressionliblinear.csv b/Model Results/TestingResultsMulti_LogisticRegressionliblinear.csv
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diff --git a/Model Results/TestingResultsMulti_RandomForestClassifier.csv b/Model Results/TestingResultsMulti_RandomForestClassifier.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 0000000..79040dd
--- /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 0000000..1c9fc35
--- /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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diff --git a/Model Results/TestingResultsMulti_SVCsigmoid.csv b/Model Results/TestingResultsMulti_SVCsigmoid.csv
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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 0000000..1a78e45
--- /dev/null
+++ b/Model Results/TestingResultsMulti_SVCsigmoid_LabelsOnly.csv
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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 0000000..c758be0
--- /dev/null
+++ b/Program Outputs/Part_A_Output_CV.txt
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+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 0000000..e7cbc39
--- /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 0000000..cf87099
--- /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 0000000..8dac092
--- /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 0000000..0aeda6d
--- /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 0000000..7f19178
--- /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 0000000..1bc7144
--- /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 0000000..f2802f4
--- /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 db1f43c..d0acdb5 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,
--
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