title: Logistic Regression mean square error
body: <p><strong>NOTE:</strong> I appreciate the massive quantity of comments suggesting that this is inappropriate to quantify model performance.  However, this is irrelevant to my error, and this error occurs for a variety of other metrics.  Also, see <a href="https://meta.stackoverflow.com/questions/254341/a-car-with-square-wheels">here</a> for the appropriate way to respond when you think the OP is "asking the wrong question"</p>
  
  <p>I have an sklearn logistic model for which I am attempting to get the RMSE.  However, when I <code>.predict_proba</code>, I get a vector of probabilities.  However, my <code>y_test</code> is in its categorical form, which <code>sklearn.linear_model.LogisticRegression</code> just sort of dealt with automagically.</p>
  
  <p>How to I reconcile these two things to get the RMSE?</p>
  
  <pre><code>&gt;&gt;&gt; sklearn.metrics.mean_squared_error(y_test, pred_proba, sample_weight=weights_test)
  ValueError: y_true and y_pred have different number of output (1!=13)
  </code></pre>