cluster2d.py 文件源码

def cluster2d(data, n_clusters):
  reduced_data = reduce_with_pca(data)

  kmeans = KMeans(n_clusters = n_clusters, random_state=0).fit(reduced_data)
  print 'K-Means'
  print collections.Counter(kmeans.labels_)
  print metrics.silhouette_score(data, kmeans.labels_)

  plot_2d_data(reduced_data, kmeans.labels_)