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examples/clustering/sklearn_clustering_with_aeon_distances.ipynb

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@@ -125,7 +125,6 @@
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"# Visualize the clustering results\n",
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"plt.figure(figsize=(10, 6))\n",
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"for label in np.unique(labels):\n",
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" cluster_data = X[labels == label] # Ensure correct slicing\n",
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" plt.plot(np.mean(cluster_data, axis=0), label=f\"Cluster {label}\", linewidth=2)\n",
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"\n",
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"plt.ylabel(\"Mean Value\")\n",
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"plt.legend(loc=\"upper right\", fontsize=\"small\", ncol=2)\n",
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"plt.grid(True)\n",
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"plt.show()\n"
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"plt.show()\n",
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" plt.plot(\n",
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" np.mean(X[labels == label], axis=0), label=f\"Cluster {label}\"\n",
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" ) # Fix indexing\n",
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"plt.title(\"Hierarchical Clustering with DTW Distance\")\n",
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"plt.legend()\n",
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"plt.show()"
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]
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},
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{

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