[pymvpa] Shrinkage LDA for PyMVPA

[Michael Bannert]

Dear PyMVPA users,

Since I couldn't find an implementation of "shrinkage LDA" (e.g., 
Pereira & Botvinick, NeuroImage, 2011) in PyMVPA, I implemented my own 
based on Gaussian Discriminant Analysis (gda.py). I figured it could be 
helpful for other users as well?

It is considerably faster than using the scikit-learn implementation 
through the SKLLearnerAdapter, which I have been using until now:

SKLLearnerAdapter(LinearDiscriminantAnalysis(solver='lsqr', 
shrinkage='auto'))

It is also a little more flexible because you can choose between the 
Ledoit-Wolf estimator and the Oracle Approximating Shrinkage.

May it be useful.

Cheers,
Michael
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