title: Is there any module for Non_Linear Logistic regression in Python sklearn?
body: <p>In the package <code>sklearn</code> available here - <a href="https://github.com/scikit-learn/scikit-learn/tree/master/sklearn" rel="nofollow noreferrer">Github/Sklearn</a> we see <code>linear_model</code> module which is very well used for <code>logistic regression</code> ML problems. I'm successful in implementing that for datasets, decision boundary of which can be separated by a straight line. But the question is how can one implement logisitc regression for <code>non-linear models</code>.</p>
  
  <p>I tried searching the library (in the above guithub link) if it contains any relevant module, but couldn't. Is there a way to deal with non-linear problems from sklearn? (apart from clustering algorithms) Are there any other library to help with non-linear regression ? Suggestions are welcome. </p>