Fast PCA(principal component analysis)
I use PCA engine to compute pca but it is very slow.Is there a fast method to compute pca?
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give more information about your task(size of the problem, number of principal components needed etc.)
features dimension = 4000 count = 20000.
PCA isn't supposed to run fast... It is an algorithm that has to calculate tons of covariance matrices, which takes time...
OpenCV''s PCA is indeed not the fastest one (at least at the time I used it, maybe it changed in the meantime). Either use a different library for that or try to use SVD instead, you basically solve the same problem there, see http://math.stackexchange.com/questions/3869/what-is-the-intuitive-relationship-between-svd-and-pca how they are related.
If you need only few first principal components you can use iterative methods (I don't know if they fast enough) some info here http://scicomp.stackexchange.com/questions/3220/fastest-pca-algorithm-for-high-dimensional-data