Hi list, I would like to ask for comments on the forests of randomized trees pull request that I have been working on for the past few weeks. I think it is ready for merge.
This pull request is the first in scikit-learn to concern ensemble methods and includes two important tree-based algorithms (RandomForest, ExtraTrees), comes with tests (100% coverage), full documentation (docstrings, narrative documentation) and an example. Criticism and comments on the code, the documentation and the example are welcomed in the pull request: https://github.com/scikit-learn/scikit-learn/pull/439 Cheers, Gilles ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
