[{'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:from sklearn.ensemble import RandomForestRegressor\nnp.random.seed(42)\n# drop target columns\ndf_original = df.copy()\ndrop_cols=['cnt', 'dteday','registered','casual']\nX = df.drop(drop_cols, axis = 1) # X = independent columns (potential predictors)\ny = df['cnt'] # y = target column (what we want to predict)\n# instantiate RandomForestClassifier\nrf_model = RandomForestRegressor()\nrf_model.fit(X,y)\nfeat_importances = pd.Series(rf_model.feature_importances_, index=X.columns)\n# determine 20 most important features\ndf_imp_feat = feat_importances.nlargest(20)\ndf_imp_feat.plot(kind='bar')\nplt.show()\nprint(df_imp_feat)\nprint('Comparing with our columns')\nprint(cols_to_remove)"}, {'role': 'assistant', 'content': "['modelling']"}]