A Core Set Weighted Support Vector Machines

Shuxia LU, Limin LI

Key Lab. In Machine Learning and Computational Intelligence College of Mathematics and Computer Science, Hebei University Baoding 071002, China

Abstract: Classification for large datasets is a classical problem in machine learning. In this paper, we focus on effevtive classification algorithm for large datasets and imbalanced datasets. First, to deal with imbalanced dataset, we define the weight according to the size of positive and negative dataset. Then, a fast learning algorithm on large datasets called a core set weighted support vector machines (CSWSVM) is proposed. In the proposed approach, the corresponding core set (CS) can be solved by employing the core vector machine (CVM) ｏｒ generalized CVM (GCVM), and then the weighted support vector machines (WSVM) can be used to implement classification for imbalanced datasets. Experimental results on UCI and USPS datasets demonstrate that the proposed method is effective.

Keywords: core vector machine; weight; support vector machine; core set