title: Passing a not-supervised learning model to cross_val_score
body: <p>What exactly is calculated when we pass something with no <code>predict</code> method to <code>cross_val_score</code>, like here</p>
  
  <pre><code>from sklearn.model_selection import cross_val_score
  from sklearn.decomposition import PCA
  # X is some data, say two dimensional numpy array of reals
  cross_val_score(PCA(n_components=10), X)
  </code></pre>
  
  <p>That is, using <code>cross_val_score</code> without <code>y</code>, and without <code>predict</code>.</p>
  
  <p>I asked it previously <a href="https://stats.stackexchange.com/questions/419723/cross-validation-score-for-pca">here</a>, but there was no reply.</p>
  
  <p>Thanks!</p>