[{'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.metrics import r2_score\nplt.plot(y_svr_test,'g--',label='SVR(fit :%0.3fs,predict:%0.3fs,r^2:%0.3f)'%(svr_fit_time,svr_predict_time,r2_score(y_svr_test,y_test)),zorder=3)\nplt.plot(y_kr_test,'b--',label='KRR(fit:%0.3fs,predict:%0.3fs,r^2:%0.3f)'%(kr_fit_time,krr_predict_time,r2_score(y_kr_test,y_test)),zorder=2)\nplt.plot(y_test,'r-',label='True data',zorder=1)\nplt.legend()\nplt.show()"}, {'role': 'assistant', 'content': "['helper_functions', 'evaluation', 'result_visualization']"}]