Logistic Regression, Random Forest, Neural Networks, Image Processing, Computer Vision.
PCA_LDA_Random(df): X_train_std, X_test_std, y_train, y_test = scaling(df) pipeline = Pipeline([('pca', PCA(n_components= 2)), ('clf', RandomForestRegressor(n_estimators=20,random_state=42))]) pipeline.fit(X_train_std, y_train) print('Test Accuracy: %.3f' %pipeline.score(X_test_std, y_test))