[{'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:from sklearn.decomposition import PCA\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import StandardScaler\nY = dataset.iloc[:, 0].values\nX = dataset.iloc[:, 1:].values\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=0)\nscaler = StandardScaler()\nX_train_std = scaler.fit_transform(X_train)\nX_test_std = scaler.fit_transform(X_test)\npca = PCA(n_components = 2)\nX_train_pca = pca.fit_transform(X_train_std)\nprint('Variance Explained Per Principal Component: ', pca.explained_variance_ratio_, end='\\n\\n')\nprint('Total Variance Explained: ', np.sum(pca.explained_variance_ratio_), end='\\n\\n')"}, {'role': 'assistant', 'content': "['helper_functions', 'data_preprocessing', 'modelling']"}]