[{'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:import time\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn.cluster import AgglomerativeClustering\nn_samples = 500\nnp.random.seed(0)\nt = 1.5 * np.pi * (1 + 3 * np.random.rand(1, n_samples))\nx = t * np.cos(t)\ny = t * np.sin(t)\nX = np.concatenate((x, y))\nX += .7 * np.random.randn(2, n_samples)\nX = X.T\nplt.scatter(X[:, 0], X[:, 1], c='blue', cmap=plt.cm.spectral)\nplt.axis('equal')\nplt.axis('off')\nplt.show()"}, {'role': 'assistant', 'content': "['helper_functions', 'load_data', 'data_exploration']"}]