regarding the kernel weight output of libsvm operator
I applied libsvm operator for several data sets, and found that the kernel weight values of the built model tend to be always positive. For instance, I can have
However, according to SVM theory, the weight vector should satisfy equation of
wx+b =0The x is the points located on the decision hyperplane. The entries in the weight vector cannot always be larger than zero. Does the weight vector output by Rapidminer has a different physical meaning than the SVM theory?