Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules

Based on analysis of data distribution rules, piecewise combination support vector machine is put forward in this paper. First, statistical analysis is adopted for the original data. Then, k-means cluster algorithm is introduced to compute cluster centers for the data. For three cases of data distribution, which is, sphere-distribution, linearly binary separable distribution, and locally linearly separable distribution, minimum enclosing and maximum excluding support vector machine, common support vector machine and local linear support vector machine are defined to solve the objective problems. Different support vector machines for different data distribution will improve classification performance.