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.


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install.packages("wSVM")

0.1-7 by SungHwan Kim, 6 years ago


Browse source code at https://github.com/cran/wSVM


Authors: SungHwan Kim and Soo-Heang Eo


Documentation:   PDF Manual  


GPL-2 license


Depends on MASS, quadprog


See at CRAN