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.


Reference manual

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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