[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def get_statistics(confusion_matrix, labels):\n"""\ncompute accuracy, mean square error and kappa\n"""\ntotal = 0.0\nrights = 0.0\nerror = 0.0\ntrue_totals = np.zeros(len(labels)+1)\npredict_totals = np.zeros(len(labels)+1)\nfor true_label in labels:\nfor predicted_label in labels:\ncurrent_val = confusion_matrix[predicted_label][true_label]\ntotal += current_val\nerror += abs(true_label-predicted_label)**2 * current_val\npredict_totals[int(predicted_label)] += current_val\ntrue_totals[int(true_label)] += current_val\nrights += confusion_matrix[true_label][true_label]\naccuracy = rights/total\nerror /= total\nef = 0.0\nfor label in labels:\nef += true_totals[int(label)]*predict_totals[int(label)]/total\nK = (rights-ef)/(total-ef)\nreturn accuracy, error, K\naccuracy, error, kappa = get_statistics(confusion_matrix, labels)\nprint("Accuracy:", accuracy)\nprint("Mean Square Error:", error)\nprint("Kappa score:", kappa )'}, {'role': 'assistant', 'content': "['evaluation', 'prediction']"}]