Fisher subspace tree classifier based on neural networks

被引：0
|
作者：
Chen, DY [1 ]
Lu, XD [1 ]
Zhang, LM [1 ]
机构：
[1] Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 2, PROCEEDINGS | 2005年 / 3497卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a multi-neural network classification based on fisher transformation. The new method improves HDR[1] (Hierarchical discriminate regression) method proposed in 2000, which can classify the training set from coarse to fine by non-linear dynamic clustering for high-dimension data. In proposed method a fisher subspace replaces K-L subspace of HDR that simplifies the Hierarchical tree. Simulation results show that our method is better than HDR on recognition ratio and time cost.
引用
收藏
页码：14 / 19
页数：6
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