2012/2/28 Brent Pedersen <[email protected]>: > Hi, > is there an example in the docs that I'm missing of using > PCA to remove batch effects?
I don't really know what you mean by batch effects but I assumes you want to get rid of low frequency components in images or sounds or noisy generic topics (such as generic stop words) in text documents. > If I understand correctly, I may be able to do this by > using U, S, V = pca._fit(X) and then removing the first n_components. > Is there a way to do this so I can then use inverse_transform > to get the data in the original projection with batch effects > removed? I think you should write your own class that derives from sklearn PCA or RandomizedPCA and implement transform and inverse_transform as you wish. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ 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
