Peekaboo

Some time ago I wrote about a structured learning project I have been working on for some time, called pystruct . After not working on it for some time, I think it has come quite a long way the last couple of weeks as I picked up work on structured SVMs again. So here is a quick update on what you can do with it. To the best of my knowledge this is the only tool with ready-to-use functionality to learn structural SVMs (or max-margin CRFs) on loopy graphs - even though this is pretty standard in the (computer vision) literature.

As you hopefully have heard, we at scikit-learn are doing a user survey (which is still open by the way). One of the requests there was to provide some sort of flow chart on how to do machine learning. As this is clearly impossible, I went to work straight away. This is the result: [edit2] clarification: With ensemble classifiers and ensemble regressors I mean random forests , extremely randomized trees, gradient boosted trees , and the soon-to-be-come weight boosted trees (adaboost). [/edit2] Needless to say, this sheet is completely authoritative.

After a little delay, the team finished work on the 0.13 release of scikit-learn. There is also a user survey that we launched in parallel with the release, to get some feedback from our users. There is a list of changes and new features on the website . You can upgrade using easy-install or pip using: pip install -U scikit-learn or easy_install -u scikit-learn There were more than 60 people contributing to this release, with 24 people having 10 commits or more. Again many improvements are behind the scenes or only slightly notable. We improved test coverage a lot and we have much more consistent parameter names now. There is now also a user guide entry for the classification metrics, and their naming was improved. This was one of the many improvements Arnaud Joly , who joined the project very recently but nevertheless wound up being the one with the second most commits in this release! Now let me get to some of the more visible highlights of this release from my pers