wSVM: Weighted SVM with boosting algorithm for improving accuracy
Version 0.1-7

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.

Package details

AuthorSungHwan Kim and Soo-Heang Eo
Date of publication2012-10-29 08:59:59
MaintainerSungHwan Kim <[email protected]>
Package repositoryView on CRAN
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wSVM documentation built on May 30, 2017, 3:26 a.m.