Is SVM resilient to noise

1 回表示 (過去 30 日間)
Diver
Diver 2016 年 5 月 9 日
回答済み: Image Analyst 2016 年 5 月 9 日
I have tranning set composed of 36 features. when I calculated "explained" value of PCA using Matlab. I notice that only the first 24 components are important.
My question is, would I gain a better accuracy (prediction) if I omit the reset of the components (the other 12 components). Or SVM is very resilient to noise which means that regardless whether I removed the other 12 components or not. performance will not change that much.

サインインしてこの質問に回答する。

採用された回答

Image Analyst
Image Analyst 2016 年 5 月 9 日
I would think it would matter where the noise was. If it's far away from the dividing line, then it doesn't make any difference. If it's close to the dividing line, then yeah, it makes a huge difference.

その他の回答 (0 件)

カテゴリ

Help Center および File Exchange で Dimensionality Reduction and Feature Extraction についてさらに検索

タグ

製品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by