CONDENSED NEAREST NEIGHBOR RULE USING THE CONCEPT OF MUTUAL NEAREST NEIGHBORHOOD

被引：87

作者：

GOWDA, KC ^{[1
]}

KRISHNA, G ^{[1
]}

机构：

[1] INDIAN INST SCI,SCH AUTOMAT,BANGALORE 560012,INDIA

来源：

IEEE TRANSACTIONS ON INFORMATION THEORY | 1979年 / 25卷 / 04期

关键词：

D O I：

10.1109/TIT.1979.1056066

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

080201 [机械制造及其自动化];

摘要：

A two-stage iterative algorithm for selecting a subset of a training set of samples for use in a condensed nearest neighbor (CNN) decision rule is introduced. The proposed method uses the concept of mutual nearest neighborhood for selecting samples close to the decision line. The efficacy of the algorithm is brought out by means of an example. © 1979 IEEE

引用

页码：488 / 490

页数：3

共 12 条

[1]

NEAREST NEIGHBOR PATTERN CLASSIFICATION [J].