Intelligent Feature Selection (with SVM or PCA)

[rodrigo.constanzo]

@rodrigo.constanzo

With PCA specifically, I always got significantly worse results afterwards though (like 20-30% worse, consistently), even if I kept a fairly high amount of PCs (20ish for a 80+ point vector), which is another reason I ruled that approach out.

This is the relevant bit from my testing before that I found in this thread:

@rodrigo.constanzo

I tested seeing how small I can get things and have OK matching.

196d → 2d = 28.9%
196d → 5d = 41.9%
196d → 8d = 44.1%
196d → 9d = 54.0%

As compared to this:

@rodrigo.constanzo

If I do the same with the 196d variant (25MFCC + 2derivs) I get 73.9% matching out of the gate.

This was pretty aggressive PCA-ing as you can see. I don’t know why I stopped at 9d as it was going up from there (say vs 20d), but I think I was comparing 196d->9d vs “raw” 21d or something along those lines. So going from 21d->20d doesn’t make much sense.