title: 2 class MLP classifier is forced to 1 output (binary classifier)
body: <p>I use MLP classifier in python with different kinds of datasets.</p>
  
  <p>When there are more than two classes, I have an equal number of outputs in the classifier. When I have 2 classes, the classifier is forced to 1 output (binary). This messes up the weights matrix as well as the interpretation of the weights.</p>
  
  <p>More specifically, for M input and N outputs the weights matrix (coefs_) is MxN, when N>2. When N=2 the weights matrix is Mx1. Is there any way to force it to two separate classes? What if I want to do Multilabel classification with only two classes?</p>
  
  <p>Thanks in advance!</p>