[{'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:%pylab inline\npylab.figure(figsize=(8, 3))\n\npylab.subplot(1,2,1)\npylab.grid(True)\npylab.xlim(-100,1100)\npylab.ylim(-100,1100)\npylab.scatter(train_labels, grid_cv.best_estimator_.predict(train_data), alpha=0.5, color = 'red')\npylab.scatter(test_labels, grid_cv.best_estimator_.predict(test_data), alpha=0.5, color = 'blue')\npylab.title('linear model')\n\npylab.subplot(1,2,2)\npylab.grid(True)\npylab.xlim(-100,1100)\npylab.ylim(-100,1100)\npylab.scatter(train_labels, estimator.predict(train_data), alpha=0.5, color = 'red')\npylab.scatter(test_labels, estimator.predict(test_data), alpha=0.5, color = 'blue')\npylab.title('random forest model')"}, {'role': 'assistant', 'content': "['result_visualization']"}]