[{'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:print(" Predicting ratings for all movies seen by users 6041 and 6042...")\nauthor_set = data.ix[data[\'UserID\'].isin([6041,6042])]\nX_author = author_set.drop([\'Rating\', \'UserID\', \'MovieID\'], axis=1).values\nY_author = author_set[\'Rating\'].values\nlabels = data[\'Rating\'].unique()\ny_pred = nb.predict(X_author)\nprint("Predicting ratings for test set. This may take a while...")\nconfusion_matrix = nb.score(X_author, Y_author, labels)\nprint("Done. Plotting the confusion matrix")\nplot_confusion_matrix(confusion_matrix, labels)\naccuracy, error, kappa = get_statistics(confusion_matrix, labels)\nprint("Accuracy:", accuracy)\nprint("Mean Square Error:", error)\nprint("Kappa score:", kappa )'}, {'role': 'assistant', 'content': 'result_visualization'}]