Feature Selection in Marketing Applications

被引：0

作者：

Lessmann, Stefan ^{[1
]}

Voss, Stefan ^{[1
]}

机构：

[1] Univ Hamburg, Inst Informat Syst, D-20146 Hamburg, Germany

来源：

ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS | 2009年 / 5678卷

关键词：

Marketing; Decision Support; Classification; Feature Selection; Support Vector Machines; MODELS;

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：

The paper is concerned with marketing applications of classification analysis. Feature selection (PS) is crucial in this domain to avoid cognitive overload of decision makers through use of excessively large attribute sets. Whereas algorithms for feature ranking have received considerable attention within the literature, a clear strategy how a subset of attributes should be selected once a ranking has been obtained is yet missing. Consequently; three candidate FS procedures are presented and contrasted by means of empirical experimentation on real-world data. The results offer some guidance which approach should be employed in practical applications and identify promising avenues for future research.

引用

页码：200 / 208

页数：9

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