[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:car_features = extract_features(car_images, cspace=color_space, orient=orient,\npix_per_cell=pix_per_cell, cell_per_block=cell_per_block,\nhog_channel=hog_channel)\nnotcar_features = extract_features(notcar_images, cspace=color_space, orient=orient,\npix_per_cell=pix_per_cell, cell_per_block=cell_per_block,\nhog_channel=hog_channel)\nX_raw = np.vstack((car_features, notcar_features)).astype(np.float64)\nX_scaler = StandardScaler().fit(X_raw)\nX_data = X_scaler.transform(X_raw)\ny_data = np.hstack((np.ones(len(car_features)), np.zeros(len(notcar_features))))\nX_data, y_data = shuffle(X_data, y_data)\nX_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size=0.2)\nprint('Data:       ',X_data.shape)\nprint('Labels:     ',y_data.shape)\nprint('Train:      ',X_train.shape)\nprint('Validation: ',X_test.shape)"}, {'role': 'assistant', 'content': 'data_preprocessing'}]