If this is the first time you contribute, please make sure to carefully read the contributors guide till the end:
http://scikit-learn.org/stable/developers/contributing.html In particular, make sure to follow the estimators API conventions for your PR to get a chance to be reviewed. In particular the gist you linked to is not compatible with the scikit-learn estimators API. Personally I have never heard of Markov clustering, so it's hard for me to assess whether it should be included in the project or not. It would really help if you could demonstrate its performance on a publicly available dataset where is does significantly better than all the other clustering algorithms already implemented in scikit-learn (both in terms of training speed and in terms of cluster quality / stability, although this latter point is very domain dependent). As a side note, if this is the first time you contribute to the project, it's probably best to have a look at how other pull requests are being reviewed (by reading the comment threads of other PRs) and maybe start by a small pull request to fix small bug (with a non-regression test) or tackle some documentation issues. Adding new estimators takes a lot of effort to review (we need tests, docs, updated examples) and assume some familiarity with the existing code base. -- Olivier _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
