title: scikit-learn return value of LogisticRegression.predict_proba
body: <p>What exactly does the <code>LogisticRegression.predict_proba</code> function return?</p>
  
  <p>In my example I get a result like this:</p>
  
  <pre><code>[[  4.65761066e-03   9.95342389e-01]
   [  9.75851270e-01   2.41487300e-02]
   [  9.99983374e-01   1.66258341e-05]]
  </code></pre>
  
  <p>From other calculations, using the sigmoid function, I know, that the second column are probabilities. The <a href="http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression.predict_proba" rel="noreferrer">documentation</a> says, that the first column are <code>n_samples</code>, but that can't be, because my samples are reviews, which are texts and not numbers. The documentation also says, that the second column are <code>n_classes</code>. That certainly can't be, since I only have two classes (namely <code>+1</code> and <code>-1</code>) and the function is supposed to be about calculating probabilities of samples really being of a class, but not the classes themselves.</p>
  
  <p>What is the first column really and why it is there?</p>