[{'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:feature = [\'num_voted_users\', \'title_year\', \'num_critic_for_reviews\', \'movie_facebook_likes\',\n\'num_user_for_reviews\', \'gross\',\'duration\',\'budget\']\ntarget = [\'imdb_score\']\nmovie_data = read_file()\nfor i in feature:\nmovie_data[i] = movie_data[i].interpolate()\nsample_MSEs = []\ndef sample_run():\ntrain, test = random_sample(movie_data)\nrandom_forest_model = RandomForestRegressor(n_estimators=150, max_features=\'sqrt\')\nrandom_forest_model.fit(train[feature], train[target].values.ravel()) #? what is ravel\npredicted = np.array(random_forest_model.predict(test[feature]))\nscore = np.array(test[target])\npredicted.resize((predicted.shape[0],1))\nresiduals = score-predicted\nreturn sorted(zip(test[\'director_name\'], residuals),key=lambda x: id(x[0]))\nresult = sample_run()\nl = [y[0] for x,y in result]\nprint(len(l))\nplt.hist(l,bins=20)\nplt.show()\ndirector_list = []\naverage_residual = []\ncnt = 0\ncurrent_sum=0.0\nfor i in range(len(result)):\nif id(result[i][0])==id(result[i-1][0]):\ncnt+=1\ncurrent_sum+=result[i][1]\nelse:\nif cnt >= 3 and (current_sum/cnt > 0.8 or current_sum/cnt < -0.8):\ndirector_list.append(result[i][0])\naverage_residual.append(current_sum/cnt)\ncnt=1\ncurrent_sum=result[i][1]\nfor d,r in zip(director_list, average_residual):\nprint(d,r)\nprint("Done")'}, {'role': 'assistant', 'content': "['load_data', 'evaluation', 'modelling', 'prediction']"}]