[{'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:from collections import Counter\ncolors = ["red", "dodgerblue", "springgreen", "orange", "magenta", "black", "maroon", "aqua", "gold"]\ndef compute_sill(X, min_clusters, max_clusters, label):\narr = []\nmax_clusters = min(X.shape[0], max_clusters)\nfor n_clusters in range(min_clusters, max_clusters+1):\nclust = MiniBatchKMeans(n_clusters=n_clusters, batch_size=1000, n_init=100)\nclust.fit(X)\npred = clust.predict(X)\narr.append(silhouette_score(X, pred))\nplt.plot(range(min_clusters, max_clusters+1), arr, label=label)\nplt.legend()\ndef clust_and_plot(X, n_clusters, sill=True):\nclust = MiniBatchKMeans(n_clusters=n_clusters, batch_size=1000, n_init=100)\nclust.fit(X)\npred = clust.predict(X)\nfig, ax = plt.subplots(1,3,figsize=(16,5))\nax[0].set_title("X")\nax[1].set_title("Y")\nax[2].set_title("Z")\npermut = np.random.permutation(range(X.shape[0]))\npred = pred[permut]\nfor i, row in enumerate(X[permut]):\nax[0].plot(range(MAX_POS+1), row[range(0, MAX_POS+1)], c=colors[pred[i]], alpha=.5)\nax[1].plot(range(MAX_POS+1), row[range(MAX_POS+1, 2*MAX_POS+2)], c=colors[pred[i]], alpha=.5)\nax[2].plot(range(MAX_POS+1), row[range(2*MAX_POS+2, 3*MAX_POS+3)], c=colors[pred[i]], alpha=.5)\nif i > 1000:\nbreak\nreturn clust.cluster_centers_,  \\\nnp.array([np.std(c - X, 0) for c in clust.cluster_centers_]), \\\npred'}, {'role': 'assistant', 'content': 'modelling'}]