On Fri, Dec 14, 2012 at 05:32:26PM +0100, federico vaggi wrote:
> What I wanted to know is:

> 1- Is there a way to efficiently calculate the covariance matrix given this
> data which isn't than manually calculating all NxN weights?

If X is you matrix, (n_samples x n_features), np.dot(X.T, X) is the
sample covariance matrix, as long as X is centered (remove the mean in
the sample direction).

G

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