title: method='predict_proba' for cross_val_predict return "index 1 is out of bounds for axis 1 with size 1"
body: <p>This is the part of the data set:</p>
  <pre><code>a b c result
  0 1 1  positive
  0 0 1  negative
  0 1 1  negative
  0 0 0  positive
  
  
  result = [1 if v=='positive' else 0 for v in data['result'].tolist()]
  
  Output = result
  X = data[&quot;a&quot;, &quot;b&quot;, &quot;c&quot;]
  y = np.reshape(Output, (X.shape[0], 1))
  </code></pre>
  <p>I am trying to use the cross-validation method in sklearn  to predict the class of X data: This part of my codes work:</p>
  <pre><code>logreg = LogisticRegression('l2')
  y_pred_class = cross_val_predict(logreg, X, y, cv=10, method= 'predict' ) 
  </code></pre>
  <p>but when I want to calculate probabily of a class using this code:</p>
  <pre><code>y_pred_prob = cross_val_predict(logreg, X, y, cv=10, method='predict_proba')
  </code></pre>
  <p>It has this error:</p>
  <pre><code>index 1 is out of bounds for axis 1 with size 1
  </code></pre>
  <p>do you know what is the problem?</p>