Clustering, Data Analysis.
print("Silhoutte Score (K-Means) -" + str(n_clusters) +" :" +str(silhoutte_avg)) data0["Clustering_Kmeans_Exp1_" + str(n_clusters)] = cluster_labels Output: for n_clusters in range(3,6): kmeans = KMeans(n_clusters = n_clusters, random_state=0) cluster_labels = kmeans.fit_predict(X_num)