Logistic Regression, Random Forest, Neural Networks, Image Processing, Computer Vision.
test_size=0.25, random_state=0, shuffle = True) my_scaler = preprocessing.StandardScaler() X_train_std = my_scaler.fit_transform(X_train) X_test_std = my_scaler.fit_transform(X_test) return X_train_std, X_test_std, y_train, y_test X_train_std, X_test_std, y_train, y_test = scaling(df) Model