"clf1 = RandomForestClassifier(n_estimators=100, max_features=70)# Linear Kernel\n",
"\n",
"#Train the model using the training sets\n",
...
...
%% Cell type:code id:314edca9 tags:
``` python
importpandasaspd
importnumpyasnp
fromsklearnimportdatasets
fromsklearn.model_selectionimporttrain_test_split
fromsklearnimportsvm,metrics
fromsklearn.linear_modelimportLogisticRegression
fromsklearn.metricsimportaccuracy_score
fromsklearn.ensembleimportRandomForestClassifier
fromsklearn.model_selectionimportcross_val_score
#Read data from a CSV file and parse it into a Pandas DataFrame
#header is an optional parameter specifying whether the CSV file contains a header line. In this task, all data needs to be loaded as content and no header line is needed
#Store the first 128 columns in data frame df as feature data in the 'df_feature ' variable and store the 128th column as label data in the 'df_label ' variable
#Use cross-validation to evaluate the performance of the classifier 'clf1 ' on the training dataset 'X_train' and the corresponding target variable 'y_train'