title: ValueError: multiclass-multioutput format is not supported using sklearn roc_auc_score function
body: <p>I am using <code>logistic regression</code> for prediction. My predictions are <code>0's</code> and <code>1's</code>. After training my model on given data and also when training on important features i.e <code>X_important_train</code> see screenshot. I am getting score around 70% but when I use <code>roc_auc_score(X,y)</code> or <code>roc_auc_score(X_important_train, y_train)</code> I am getting value error:
   <code>ValueError: multiclass-multioutput format is not supported</code></p>
  
  <p>Code:</p>
  
  <pre><code># Load libraries
  from sklearn.linear_model import LogisticRegression
  from sklearn import datasets
  from sklearn.preprocessing import StandardScaler
  from sklearn.metrics import roc_auc_score
  
  # Standarize features
  scaler = StandardScaler()
  X_std = scaler.fit_transform(X)
  
  # Train the model using the training sets and check score
  model.fit(X, y)
  model.score(X, y)
  
  model.fit(X_important_train, y_train)
  model.score(X_important_train, y_train)
  
  roc_auc_score(X_important_train, y_train)
  </code></pre>
  
  <p>Screenshot:</p>
  
  <p><a href="https://i.stack.imgur.com/uEVJX.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/uEVJX.png" alt="enter image description here"></a></p>