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| Design of Multicolor Voronoi Classifier with Gradually Local Learning Ablility |
| Pei Ji-hong①; Yang Xuan② |
| ①Modern Education Tech. and Info. Center Shenzhen Univ., Shenzhen 518060 China;②School of lnfo. and Eng., Shenzhen 518060 China |
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Abstract A novel MultiColor Voronoi Classifier (MCVC) is proposed, which can be ap-plied 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.
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Received: 10 June 2003
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2004, Vol. 26 
