title: AdaBoost with gridsearch can't use permutation_test_score
body: <p>I'm trying to evaluate the performance of my AdaBoosted decision tree against random chance.</p>
  
  <pre><code>dcf = AdaBoostClassifier(DecisionTreeClassifier(max_depth=2,  
  max_features="auto", min_samples_split=3, 
  min_samples_leaf=14), 
  algorithm="SAMME",random_state=123)
  clf = GridSearchCV(dcf, param_grid, scoring='accuracy', cv=5)
  
  clf.fit(train_dat, train_labels)
  </code></pre>
  
  <p>However, when I want to add a permutation test:</p>
  
  <pre><code>score, permutation_scores, pvalue = permutation_test_score(
  clf.best_estimator_, test_dat,test_labels, scoring="accuracy", cv=5, n_permutations=600, n_jobs=1)
  </code></pre>
  
  <p>my error is:</p>
  
  <pre><code>Traceback (most recent call last):
    File "adaboost-test.py", line 99, in &lt;module&gt;
      clf.best_estimator_, test_dat,test_labels, scoring="accuracy", cv=5, n_permutations=600, n_jobs=1)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/model_selection/_validation.py", line 1092, in permutation_test_score
      score = _permutation_test_score(clone(estimator), X, y, groups, cv, scorer)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/model_selection/_validation.py", line 1109, in _permutation_test_score
      estimator.fit(X_train, y_train)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/ensemble/weight_boosting.py", line 427, in fit
      return super().fit(X, y, sample_weight)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/ensemble/weight_boosting.py", line 150, in fit
      random_state)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/ensemble/weight_boosting.py", line 490, in _boost
      random_state)
    File "/usr/local/lib/python3.5/dist-packages/sklearn/ensemble/weight_boosting.py", line 579, in _boost_discrete
      raise ValueError('BaseClassifier in AdaBoostClassifier '
  ValueError: BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble can not be fit.
  </code></pre>