Hello,
The previous email, mentioned PCA and ICA and their kernel counter parts.
Like it sauid, its a good place to start from. But their effectiveness
highly depends on how noisy your dataset is and how large is the number of
features.
SVM-RFE by Isabelle Guyon is known to be very good. Another
Hello,
I think that the problem is too complex and open to expect to find a tool
that does the job. The question of what constitutes an
interesting/relevant/useful feature for clustering is hard to answer. One
approach is to go for feature extraction (dimensionality reduction) rather
than feature
Well, you can use PCA which is a standard tool. (Of course, depending on
your problem and the nature and quality of the features the results may range
from great to catastrophic). In any case, that's what I'd try first.
Another option would be ICA but you need to satisfy some additional statisti
