title: What exactly does `eli5.show_weights` display for a classification model?
body: <p>I used <code>eli5</code> to apply the permutation procedure for feature importance. In the <a href="https://eli5.readthedocs.io/en/latest/blackbox/permutation_importance.html" rel="nofollow noreferrer">documentation</a>, there is some explanation and a small example but it is not clear.</p>
  
  <p>I am using a <code>sklearn SVC</code> model for a classification problem.</p>
  
  <p><strong>My question is:</strong> Are these weights the change (decrease/increase) of the accuracy when the specific feature is shuffled OR is it the SVC weights of these features?</p>
  
  <p>In <a href="https://medium.com/towards-artificial-intelligence/how-to-use-scikit-learn-eli5-library-to-compute-permutation-importance-9af131ece387" rel="nofollow noreferrer">this medium article</a>, the author states that these values show the <em>reduction in model performance by the reshuffle of that feature.</em> But not sure if that's indeed the case.</p>
  
  <p>Small example:</p>
  
  <pre class="lang-py prettyprint-override"><code>from sklearn import datasets
  import eli5
  from eli5.sklearn import PermutationImportance
  from sklearn.svm import SVC, SVR
  
  # import some data to play with
  iris = datasets.load_iris()
  X = iris.data[:, :2]
  y = iris.target
  
  clf = SVC(kernel='linear')
  perms = PermutationImportance(clf, n_iter=1000, cv=10, scoring='accuracy').fit(X, y)
  
  print(perms.feature_importances_)
  print(perms.feature_importances_std_)
  
  [0.38117333 0.16214   ]
  [0.1349115  0.11182505]
  
  eli5.show_weights(perms)
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/UvjdG.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/UvjdG.png" alt="enter image description here"></a></p>