[{'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:tfidf = TfidfVectorizer(<br>\\tmin_df=1, max_features=1600, strip_accents='unicode',lowercase =True,<br>\\tanalyzer='word', token_pattern=r'\\\\w+', ngram_range=(1, 3), use_idf=True, <br>\\tsmooth_idf=True, sublinear_tf=True, stop_words = 'english')<br>X_train = tfidf.fit_transform(train['Text']).toarray()<br>print(X_train)<br>X_test = tfidf.fit_transform(test['Text']).toarray()<br><br>def encoding(df,col):<br>    le = LabelEncoder()<br>    for i in col:<br>        df[i] = le.fit_transform(df[i])<br>train.columns<br>col = ['Gene', 'Variation', 'Class']<br>encoding(train,col)<br>encoding(test,['Gene', 'Variation'])<br><br>X_train = pd.DataFrame(X_train)<br>X_train = X_train.join(train[['Gene', 'Variation', 'Text_no_word','Text_no_char']]) <br>X_test = pd.DataFrame(X_test)<br>X_test = X_test.join(test[['Gene', 'Variation', 'Text_no_word','Text_no_char']])"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]