On 8-Jun-09, at 1:17 AM, David Cournapeau wrote: > I would not be surprised if David had this paper in mind :) > > http://www.cs.toronto.edu/~roweis/papers/empca.pdf
Right you are :) There is a slight trick to it, though, in that it won't produce an orthogonal basis on its own, just something that spans that principal subspace. So you typically have to at least extract the first PC independently to uniquely orient your basis. You can then either subtract off the projection of the data on the 1st PC and find the next one, one at at time, or extract a spanning set all at once and orthogonalize with respect to the first PC. David _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
