[{'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.linear_model import LinearRegression\nfrom sklearn.model_selection import train_test_split\n\nX = X_df[['URL_distance_token_sort_ratio', 'URL_distance_levenshtein', 'URL_distance_jaro_winkler', 'Text-length', 'referred-expression']]\ny = X_df['y']\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=23)\n\nX_train_features = X_train.drop(columns='referred-expression')\nX_train_referred_expression = X_train['referred-expression']\n\nX_test_features = X_test.drop(columns='referred-expression')\nX_test_referred_expression = X_test['referred-expression']\n\nlr = LinearRegression(normalize=True).fit(X_train_features, y_train)\n\ny_pred_ = lr.predict(X_test_features)"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]