Multiple birth least squares support vector machine for multi-class classification

作者：Chen, Su-Gen; Wu, Xiao-Jun^*

来源：International Journal of Machine Learning and Cybernetics, 2017, 8(6): 1731-1742.

DOI：10.1007/s13042-016-0554-7

• Multi-class classification
• Least squares
• Twin support vector machine
• Multiple birth least squares support vector machine

Least squares twin support vector machine (LSTSVM) was initially designed for binary classification. However, practical problems often require the discrimination more than two categories. To tackle multi-class classification problem, a novel algorithm, called multiple birth least squares support vector machine (MBLSSVM), is proposed. Our MBLSSVM solves K quadratic programming problems (QPPs) to obtain K hyperplanes, each problem is similar to binary LSTSVM. Comparison against the Multi-LSTSVM, Multi-TWSVM, MBSVM and our MBLSSVM on both UCI datasets and ORL, YALE face datasets illustrates the effectiveness of the proposed method.

• 出版日期2017-12
• 单位安庆师范大学; 江南大学