# Intelligent Feature Selection (with SVM or PCA)

**URL:** <https://discourse.flucoma.org/t/intelligent-feature-selection-with-svm-or-pca/788>\
**Category:** Code Sharing\
**Created:** [February 23, 2021, 12:59pm UTC](https://discourse.flucoma.org/t/intelligent-feature-selection-with-svm-or-pca/788 "2021-02-23T12:59:26Z")\
**Posts on this page:** 1\
**Showing post:** 20

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**Author:** ![rodrigo.constanzo](https://discourse.flucoma.org/user_avatar/discourse.flucoma.org/rodrigo.constanzo/32/12_2.png) [@rodrigo.constanzo](https://discourse.flucoma.org/u/rodrigo.constanzo)\
**Post date:** [March 1, 2021, 2:54pm UTC](https://discourse.flucoma.org/t/intelligent-feature-selection-with-svm-or-pca/788/20 "2021-03-01T14:54:40Z")

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> [@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](https://discourse.flucoma.org/t/regression-classification-regressification/547/38):

> [@Regression + Classification = Regressification?](https://discourse.flucoma.org/t/regression-classification-regressification/547/38):
>
> 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:

> [@Regression + Classification = Regressification?](https://discourse.flucoma.org/t/regression-classification-regressification/547/38):
>
> 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.

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