[{'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:def plot_prediction(test, test_pred, train, train_pred, convert_to_original_form = False):\n    if convert_to_original_form:\n        test = inv_boxcox(test, fitted_lambda),\n        test_pred = inv_boxcox(test_pred, fitted_lambda)\n        train = inv_boxcox(train, fitted_lambda),\n        train_pred = inv_boxcox(train_pred, fitted_lambda)\n    f, ax = plt.subplots(1,2, figsize=(10, 5))\n    ax1 = plt.subplot(1,2,1)\n    sns.distplot(test, hist=True, kde=True, \n             color = \'darkblue\', \n             hist_kws={\'edgecolor\':\'black\'},\n             kde_kws={\'linewidth\': 4}, ax = ax1)\n    sns.distplot(test_pred, hist=True, kde=True, \n             color = \'red\', \n             hist_kws={\'edgecolor\':\'red\'},\n             kde_kws={\'linewidth\': 4}, ax = ax1)\n    ax1.set_title("Actual vs Predicted (Test)")\n    \n    ax2 = plt.subplot(1,2,2)\n    sns.distplot(train, hist=True, kde=True, \n             color = \'darkblue\', \n             hist_kws={\'edgecolor\':\'black\'},\n             kde_kws={\'linewidth\': 4}, ax = ax2)\n    sns.distplot(train_pred, hist=True, kde=True, \n             color = \'red\', \n             hist_kws={\'edgecolor\':\'red\'},\n             kde_kws={\'linewidth\': 4}, ax = ax2)\n    ax2.set_title("Actual vs Predicted (Train)")\''}, {'role': 'assistant', 'content': "['result_visualization']"}]