[{'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:import sklearn\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.model_selection import cross_val_score\nrange1 = np.zeros(50)\nrange2 = np.zeros(50)\nfor i in range(50):\nforest = RandomForestClassifier( n_estimators = 100, max_depth=None, min_samples_split=10)\nprint("Fitting a random forest to labeled training data...")\nforest = forest.fit( train_set_x, train_set_y )\nprint(np.sqrt(np.mean(forest.predict(train_set_x)-train_set_y)**2))\nrange2[i] = np.sqrt(np.mean(forest.predict(train_set_x)-train_set_y)**2)\nresult = forest.predict( test_set_x )\nprint(np.sqrt(np.mean(result-test_set_y)**2))\nrange1[i] = np.sqrt(np.mean(result-test_set_y)**2)'}, {'role': 'assistant', 'content': 'modelling'}]