How to add an sklearn wrapper for a new ML algorithm

Question

I would like to integrate factorization machines in sklearn. I checked sklearn documentation and the web for how to wrap a new algorithm but this requirement seems to be not very well documented.

So, I would like to ask on whether there is a documentation on how to add a new algorithm wrapper to sklearn (besides reading the source code)?

Answer 1

After working through the sklearn documentation, the best thing to do is to look through a complete working example.

The XGBoost module has a thorough sklearn wrapper, which you can see here:

https://github.com/dmlc/xgboost/blob/master/python-package/xgboost/sklearn.py