[{'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:colors = [\'pink\', \'green\', \'midnightblue\', \'orange\', \'darkgrey\']<br><br># Find points belonging to each category and plot them<br>for category, category_id in sorted(category_to_id.items()):<br>    points = projected_features[(labels[indices] == category_id).values]<br>    plt.scatter(points[:, 0], points[:, 1], s=30, c=colors[category_id], label=category)<br>plt.title("tf-idf feature vector for each article, projected on 2 dimensions.",<br>          fontdict=dict(fontsize=15))<br>plt.legend()'}, {'role': 'assistant', 'content': 'result_visualization'}]