Evolutionary subspace pursuit

被引：0

作者：

Wallet, BC ^{[1
]}

Marchette, DJ ^{[1
]}

Wegman, EJ ^{[1
]}

机构：

[1] USN, Ctr Surface Warfare, Syst Res & Technol Dept, Dahlgren, VA 22448 USA

来源：

MINING AND MODELING MASSIVE DATA SETS IN SCIENCE, ENGINEERING, AND BUSINESS WITH A SUBTHEME IN ENVIRONMENTAL STATISTICS | 1997年 / 29卷 / 01期

关键词：

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We develop a method for using a genetic algorithm for performing local dimensionality reduction. Lower dimensional linear subspaces are found which most closely fit data in a higher dimensional space. Data points are then projected orthogonally to the appropriate subspace. This allows for dimensionality reduction while still preserving the local structure. Our method is applied to a number of artificial data sets, and we discuss how this method could be used for discriminant analysis, clustering, and exploratory data analysis.

引用

页码：402 / 406

页数：5

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