cols_list.append(cols) data.scale_data(cols_list[:-1]) cols_list = data.get_cols() y_column_name = input("enter y column name: ") X_train, X_test, y_train, y_test = data.spilt_data(y_column_name) model_type = input("Enter R for Regression and C for Classification: ") if model_type == "C": print("Your options are: " + str(Classifier_list)) #add mode list modelname = input("Enter model to be used: ") classifier = Classification(X_train, X_test, y_train, y_test, modelname) classifier.predict() classifier.accuracy() classifier.save_model() elif model_type == 'R': print("Your options are: " + str(Regressor_list)) #add mode list modelname = input("Enter model to be used, use A for all") if modelname == "A": for modelname in Regressor_list: regressor = Regression(X_train, X_test, y_train, y_test, modelname) regressor.predict() regressor.accuracy() regressor.save_model() else: regressor = Regression(X_train, X_test, y_train, y_test, modelname) regressor.predict() regressor.accuracy() regressor.save_model()