  In this paper, we have considered general k-piece-wise linear convex loss
functions in SVM model for measuring the empirical risk. The resulting
k-Piece-wise Linear loss Support Vector Machine (k-PL-SVM) model is an adaptive
SVM model which can learn a suitable piece-wise linear loss function according
to nature of the given training set. The k-PL-SVM models are general SVM models
and existing popular SVM models, like C-SVM, LS-SVM and Pin-SVM models, are
their particular cases. We have performed the extensive numerical experiments
with k-PL-SVM models for k = 2 and 3 and shown that they are improvement over
existing SVM models.
