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Can discrete wavelet trasform be used for feature extraction from time series in order to cluster them? Any R code how to do this will be appreciated.

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1 Answer

Yes it can.

Any kind of feature extraction is a good idea for clustering. Go ahead, and try some of them.

If you can define a good distance function on your wavelet transformed data, then most distance based clustering algorithms should work for you.

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Ok, but how to extract relevant features? Are all wavelet coefficients relevant? Or only some of them? – Miroslav Sabo Oct 9 '12 at 17:16
Depends on your data and domain. Sometimes they are, sometimes they aren't. Try different things. – Anony-Mousse Oct 9 '12 at 19:08

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