wSVM-package: Weigthed SVM with boosting algorithm for improving accuracy

In wSVM: Weighted SVM with boosting algorithm for improving accuracy

Description

We propose weighted SVM methods with penalization form. By adding weights to loss term, we can build up weighted SVM easily and examine classification algorithm properties under weighted SVM. Through comparing each of test error rates, we conclude that our Weighted SVM with boosting has predominant properties than the standard SVM have, as a whole.

Details

Package:	wSVM
Type:	Package
Version:	0.1-7
Date:	2010-10-03
License:	GPL-2
LazyLoad:	yes

Author(s)

SungHwan Kim [e-mail]
Soo-heang Eo [e-mail]

See Also

wsvm, wsvm.predict, wsvm.boost

wSVM documentation built on May 2, 2019, 12:24 p.m.