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

来源：

PATTERN RECOGNITION | 2007年 / 40卷 / 05期

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

页码：1486 / 1497

页数：12

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