[{'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:import pandas as pd\nimport nltk, re, string\nimport numpy as np\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.feature_extraction.text import TfidfTransformer\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.feature_selection import SelectKBest, chi2\nfrom sklearn import svm\nfrom nltk.corpus import stopwords\nfrom sklearn import linear_model\nfrom sklearn.naive_bayes import MultinomialNB\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.metrics import classification_report\nfrom sklearn.preprocessing import scale\nfrom sklearn.metrics import confusion_matrix\nimport sklearn.metrics as metrics\nimport itertools\n%matplotlib inline\nimport matplotlib.pyplot as plt\nfrom sklearn.ensemble import VotingClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nimport glove #Installing glove on mac seemed non-trivial. Running it on Linux, pickling results for further use.\nimport pickle\nfrom sklearn.manifold import TSNE\nimport matplotlib.pyplot as plt'}, {'role': 'assistant', 'content': "['helper_functions']"}]