Hi list, I'd like to ask for comments on the GraphLasso pull request that I have put in. I think that it is ready for merge, even though it has been in development for a short amount of time, because I have been working on similar algorithms for more than two years.
To give you a run-through, and try to interest you, the algorithm implemented is a covariance learning algorithm, but it is particularly useful to recover a graph of conditional independence from empirical data. To apply it on real data (other than brain data, which is what I do), I have adapted the example where we do unsupervised learning on the stock market: https://github.com/GaelVaroquaux/scikit-learn/blob/glasso/examples/applications/plot_stock_market.py I find that the result is really cool: http://www.flickr.com/photos/66885349@N03/6328041585/sizes/l/in/photostream/ I welcome criticism and comments on the code, the documentation and the examples in the pull request: https://github.com/scikit-learn/scikit-learn/pull/431 Gael ------------------------------------------------------------------------------ RSA(R) Conference 2012 Save $700 by Nov 18 Register now http://p.sf.net/sfu/rsa-sfdev2dev1 _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
