title: scikit-learn: Finding the features that contribute to each KMeans cluster
body: <p>Say you have 10 features you are using to create 3 clusters. Is there a way to see the level of contribution each of the features have for each of the clusters?</p>
  
  <p>What I want to be able to say is that for cluster k1, features 1,4,6 were the primary features where as cluster k2's primary features were 2,5,7.</p>
  
  <p>This is the basic setup of what I am using:</p>
  
  <pre class="lang-py prettyprint-override"><code>k_means = KMeans(init='k-means++', n_clusters=3, n_init=10)
  k_means.fit(data_features)
  k_means_labels = k_means.labels_
  </code></pre>