[{'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 os\nimport pandas as pd\nimport numpy as np\nimport scipy\nimport warnings\nwarnings.filterwarnings(action=\'ignore\')\n\n# Plotting Library\nimport seaborn as sns \nimport matplotlib.pyplot as plt \nplt.style.use(\'Solarize_Light2\')\n\n# Other Libraries\nfrom sklearn.linear_model import LinearRegression \nfrom sklearn.metrics import mean_squared_error\nfrom math import sqrt\nfrom scipy.stats import ttest_ind ,linregress , ttest_rel\nimport statsmodels.api as sm\nfrom scipy.stats import probplot\nfrom scipy.stats import zscore\nfrom sklearn.metrics import r2_score\nfrom statsmodels.graphics.regressionplots import influence_plot\nfrom sklearn.preprocessing import PolynomialFeatures , StandardScaler\nfrom sklearn.pipeline import Pipeline\nfrom sklearn.decomposition import PCA\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.linear_model import Perceptron\nfrom sklearn.linear_model import Ridge\nfrom sklearn.linear_model import Lasso ,ElasticNet\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.model_selection import train_test_split\nprint(os.listdir("../input"))\''}, {'role': 'assistant', 'content': "['helper_functions']"}]