title: Does GridSearchCV not support multi-class?
body: <p>I tried to use GridSearchCV for multi-class case based on the answer from here:</p>
  
  <p><a href="https://stackoverflow.com/questions/31109192/accelerating-the-prediction/31125749?noredirect=1#comment50490112_31125749">Accelerating the prediction</a></p>
  
  <p>But I got value error, <code>multiclass format is not supported.</code></p>
  
  <p>How can I use this method for multi-class case?</p>
  
  <p>Following code is from the answer in above link.</p>
  
  <pre><code>import numpy as np
  from sklearn.datasets import make_classification
  from sklearn.preprocessing import StandardScaler
  from sklearn.svm import SVC
  from sklearn.pipeline import make_pipeline
  from sklearn.grid_search import GridSearchCV
  from sklearn.metrics import accuracy_score, recall_score, f1_score, roc_auc_score, make_scorer
  
  X, y = make_classification(n_samples=3000, n_features=5, weights=[0.1, 0.9, 0.3])
  
  pipe = make_pipeline(StandardScaler(), SVC(kernel='rbf', class_weight='auto'))
  
  param_space = dict(svc__C=np.logspace(-5,0,5), svc__gamma=np.logspace(-2, 2, 10))
  
  accuracy_score, recall_score, roc_auc_score
  my_scorer = make_scorer(roc_auc_score, greater_is_better=True)
  
  gscv = GridSearchCV(pipe, param_space, scoring=my_scorer)
  gscv.fit(X, y)
  
  print gscv.best_params_
  </code></pre>