On Thu, Feb 2, 2012 at 7:17 PM, Gael Varoquaux <[email protected]> wrote: > Just a heads up: I am going to merge in label propagation > https://github.com/scikit-learn/scikit-learn/pull/547 in the next hour > unless somebody has concerns with the code.
I personally don't like using -1 to encode unlabeled data. I would prefer np.nan (which require y to be np.float) or -2 (if you prefer y to be np.int). -1 is commonly used to encode the negative class in binary classification so it's confusing. Moreover, for Naive Bayes, it would be very natural to use the same class for the supervised and semi-supervised settings. In the absence of unlabeled data, the algorithm can downgrade gracefully to supervised learning. Therefore, it would be better not to use a label encoding which is commonly used in supervised learning. Mathieu ------------------------------------------------------------------------------ Keep Your Developer Skills Current with LearnDevNow! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-d2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
