wSVM: Weighted SVM with boosting algorithm for improving accuracy

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
MaintainerSungHwan Kim <>
Package repositoryView on CRAN
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wSVM documentation built on May 2, 2019, 12:24 p.m.