[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:# Ignore  the warnings\nimport warnings\nwarnings.filterwarnings('always')\nwarnings.filterwarnings('ignore')\n\n# data visualisation and manipulation\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom matplotlib import style\nimport seaborn as sns\nimport missingno as msno\n#configure\n# sets matplotlib to inline and displays graphs below the corressponding cell.\n% matplotlib inline  \nstyle.use('fivethirtyeight')\nsns.set(style='whitegrid',color_codes=True)\n\n#import the necessary modelling algos.\n\n#classifiaction.\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.svm import LinearSVC,SVC\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.ensemble import RandomForestClassifier,GradientBoostingClassifier\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.naive_bayes import GaussianNB\n\n#regression\nfrom sklearn.linear_model import LinearRegression,Ridge,Lasso,RidgeCV\nfrom sklearn.ensemble import RandomForestRegressor,BaggingRegressor,GradientBoostingRegressor,AdaBoostRegressor\nfrom sklearn.svm import SVR\nfrom sklearn.neighbors import KNeighborsRegressor\n\n#model selection\nfrom sklearn.model_selection import train_test_split,cross_validate\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import GridSearchCV\n\n#evaluation metrics\nfrom sklearn.metrics import mean_squared_log_error,mean_squared_error, r2_score,mean_absolute_error # for regression\nfrom sklearn.metrics import accuracy_score,precision_score,recall_score,f1_score  # for classification"}, {'role': 'assistant', 'content': 'helper_functions'}]