Design of Multicolor Voronoi Classifier with Gradually Local Learning Ablility
具有渐进局部学习特性的多色Voronoi分类器设计

A novel MultiColor Voronoi Classifier(MCVC)is proposed, which can be applied to linear and nonlinear classification problems. MCVC has sound ability to expend classification plane between samples. With increment of samples, it can be shown that the classification plane of MCVC can close to any classification function. MCVC has very good local ability too. When new learning sample is added, only local classification planed is modified and the whole classification characteristics are not modified greatly. So MCVC can solve the overfitting problem of neural network. Experiments show that MCVC is feasible to linear classification and nonlinear classification problems.