wsvm.kernel


    This function is to compute kernel K(X, U).


 internal

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.

wsvm.kernel: Compute kernel K(X, U)

Description

Usage

Arguments

See Also