Hi there! I would like to use a shrinkage LDA classifier (that is, LDA with Ledoit-Wolf covariance estimation). However, I have only found the two necessary ingredients in separate modules/classes: sklearn.lda.LDA and sklearn.covariance.LedoitWolf.
What would be the recommended way to combine these two into a shrinkage LDA classifier? Should I create a new class sklearn.lda.sLDA? Unfortunately, I cannot just modify the existing LDA class, because it uses SVD and not explicit covariance estimators to implement LDA. Would it make sense to implement an alternative LDA which uses direct estimations of covariance matrices? Then the user could use any type of regularization offered by sklearn.covariance to produce a regularized LDA classifier. Thanks in advance, Clemens ------------------------------------------------------------------------------ Android apps run on BlackBerry 10 Introducing the new BlackBerry 10.2.1 Runtime for Android apps. Now with support for Jelly Bean, Bluetooth, Mapview and more. Get your Android app in front of a whole new audience. Start now. http://pubads.g.doubleclick.net/gampad/clk?id=124407151&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
