Is there any solution to make positive semi-definite covariance matrix?
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K M Ibrahim Khalilullah
am 5 Jul. 2016
Kommentiert: Walter Roberson
am 5 Jul. 2016
I have image data. row of the data represents pixel and column represents rgb values. that is, the size of the data is N by 3. However, I would like to apply kmeans and GMM for clustering. But the covariance matrix is not positive semi-definite.
Why and what is solution?
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Walter Roberson
am 5 Jul. 2016
Covariance matrices of real variables are always positive semi-definite. See http://math.stackexchange.com/questions/114072/what-is-the-proof-that-covariance-matrices-are-always-semi-definite
If you calculated a covariance matrix but it is being reported as not positive semi-definite then you might have encountered numeric round-off. In such a case use
(X.' + X) / 2
in place of X: this will eliminate any round-off error that is keeping the matrix from being completely symmetric.
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