Extended nearest feature line classifier

被引：0

作者：

Zhou, YL ^{[1
]}

Zhang, CS ^{[1
]}

Wang, JC ^{[1
]}

机构：

[1] Tsing Hua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

PRICAI 2004: TRENDS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2004年 / 3157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：

An extended nearest feature line (ENFL) classifier is proposed to handle the discrimination problems. The ENFL borrows the concept of feature line spaces from the nearest feature line (NFL) method, to make use of the information implied by the interaction between each pair of points in the same class. Instead of the NFL distance, a better distance metric is designed in the ENFL. The ENFL is very effective in the cases with a small training set. The experimental evaluation shows that in the given feature space, the ENFL consistently achieves better performance than NFL and conventional nearest neighbor methods.

引用

页码：183 / 190

页数：8