[{'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:test = pd.read_csv("../input/test.csv")<br>test_x = test.iloc[:, 2:].values<br>imp = Imputer(missing_values = \'NaN\', strategy = \'mean\', axis = 0)<br>imp=imp.fit(test_x)<br>test_x = imp.transform(test_x)<br>dataset = pd.read_csv("../input/train.csv")<br>print(dataset.info())<br>X = dataset.iloc[:, 2:-1].values<br>imputer = Imputer(missing_values = \'NaN\', strategy = \'mean\', axis = 0)<br>input_dim = X.shape[1]<br>imputer = imputer.fit(X)<br>X = imputer.transform(X)<br>y = dataset.iloc[:, 21].values<br><br>#Standard<br>sc = StandardScaler()<br>X_train = sc.fit_transform(X)<br>x_test = sc.transform(test_x)<br>#//////////////////////<br><br>#quantile_transformer = preprocessing.QuantileTransformer(random_state=0)<br>#Xprime = quantile_transformer.fit_transform(X)<br>#txprime = quantile_transformer.transform(test_x)<br>#///////////////<br>Xtrain = preprocessing.normalize(X_train, norm=\'l2\')<br>Xtest = preprocessing.normalize(x_test, norm=\'l2\')<br>#/////////////<br># from sklearn.preprocessing import PolynomialFeatures<br># poly = PolynomialFeatures(2)<br># Xprime = poly.fit_transform(X)<br># tsprime = poly.transform(test_x)<br>#/////////////////<br># pca = PCA(n_components=2)<br># Xprime=pca.fit_transform(Xprime)<br># tsprime = pca.fit_transform(test_x)<br># print(Xprime.shape)<br># print(tsprime)<br>#////////////////////<br><br>print(X)<br>print(y)<br>print(test_x)'}, {'role': 'assistant', 'content': 'data_preprocessing'}]