  In the process of training Support Vector Machines (SVMs) by decomposition
methods, working set selection is an important technique, and some exciting
schemes were employed into this field. To improve working set selection, we
propose a new model for working set selection in sequential minimal
optimization (SMO) decomposition methods. In this model, it selects B as
working set without reselection. Some properties are given by simple proof, and
experiments demonstrate that the proposed method is in general faster than
existing methods.
