Feature space theory - a mathematical foundation for data mining

被引：70
|
作者：
Li, HX [1 ]
Xu, LD
机构：
[1] Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China
[2] Wright State Univ, Dept Management Sci & Informat Syst, Dayton, OH 45435 USA
[3] Univ Sci & Technol China, Beijing 101408, Peoples R China
来源：
KNOWLEDGE-BASED SYSTEMS | 2001年 / 14卷 / 5-6期
关键词：
knowledge representation; data mining; features; feature space; feature construction; feature selection; feature reduction; relevance analysis;
D O I：
10.1016/S0950-7051(01)00103-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In data mining, an important task in classification and prediction includes feature construction, feature description, feature selection. feature relevance analysis and feature reduction. In this paper, feature space theory is introduced as a mathematical foundation for feature related concepts and techniques in data mining, (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：253 / 257
页数：5
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