A Novel Model of Working Set Selection for SMO Decomposition Methods

Details A Novel Model of Working Set Selection for SMO Decomposition Methods A Novel Model of Working Set Selection for SMO Decomposition Methods

2007-06-05

arxiv.org/abs/0706.0585v1

Computer Science

Learning

8 pages, 12 figures, it was submitted to IEEE International conference of Tools on Artificial Intelligence

Scientific paper

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.

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