Rectified nearest feature line segment for pattern classification

被引:30
作者
Du, Hao [1 ]
Chen, Yan Qiu [1 ]
机构
[1] Fudan Univ, Dept Comp Sci & Engn, Sch Informat Sci & Engn, Shanghai 200433, Peoples R China
基金
中国国家自然科学基金;
关键词
pattern classification; nearest feature line; rectified nearest feature line segment; distribution concentration; interpolation and extrapolation accuracy;
D O I
10.1016/j.patcog.2006.10.021
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 points out and analyzes the advantages and drawbacks of the nearest feature line (NFL) classifier. To overcome the shortcomings, a new feature subspace with two simple and effective improvements is built to represent each class. The proposed method, termed rectified nearest feature line segment (RNFLS), is shown to possess a novel property of concentration as a result of the added line segments (features), which significantly enhances the classification ability. Another remarkable merit is that RNFLS is applicable to complex tasks such as the two-spiral distribution, which the original NFL cannot deal with properly. Finally, experimental comparisons with NFL, NN(nearest neighbor), k-NN and NNL (nearest neighbor line) using both artificial and real-world data-sets demonstrate that RNFLS offers the best performance. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1486 / 1497
页数:12
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