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May 3, 2019 19:52
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| from sklearn.cluster import KMeans | |
| sse={} | |
| tx_recency = tx_user[['Recency']] | |
| for k in range(1, 10): | |
| kmeans = KMeans(n_clusters=k, max_iter=1000).fit(tx_recency) | |
| tx_recency["clusters"] = kmeans.labels_ | |
| sse[k] = kmeans.inertia_ | |
| plt.figure() | |
| plt.plot(list(sse.keys()), list(sse.values())) | |
| plt.xlabel("Number of cluster") | |
| plt.show() |
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