Least Squares Twin SVM Based on Partial Binary Tree Algorithm

Abstract

Based on the classic least squares twin support vector machine (LSTSVM), an efficient but simple Least Squares Twin Support Vector Machine-Partial Binary Tree (LSTSVM-PBT)for binary classification problem was proposed. This algorithm introduces binary tree into LSTSVM, the problem summed up as binary tree classification for each data ultimately. Compared to traditional SVM, LSTSVM-PBT has low time complexity. Reliable theoretical analysis and extensive experiments show that LSTBSVM-PBT is fast computationally and obtain the higher performance than traditional algorithm.