Feature selection via discretization

被引：200

作者：

Liu, H

Setiono, R

机构：

[1] Department of Information Systems and Computer Science, National University of Singapore, Kent Ridge

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 1997年 / 9卷 / 04期

关键词：

discretization; feature selection; pattern classification;

D O I：

10.1109/69.617056

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Discretization can turn numeric attributes into discrete ones. Feature selection can eliminate some irrelevant and/or redundant attributes. Chi2 is a simple and general algorithm that uses the chi 2 statistic to discretize numeric attributes repeatedly until some inconsistencies are found in the data. It achieves feature selection via discretization. It can handle mixed attributes, work with multiclass data, and remove irrelevant and redundant attributes.

引用

页码：642 / 645

页数：4

共 12 条

[1] LEARNING BOOLEAN CONCEPTS IN THE PRESENCE OF MANY IRRELEVANT FEATURES
ALMUALLIM, H
DIETTERICH, TG
[J]. ARTIFICIAL INTELLIGENCE, 1994, 69 (1-2) : 279 - 305
[2] [Anonymous], 1992, The Tenth National Conference on Artificial Intelligence
[3] [Anonymous], P 10 NAT C ART INT S
[4] Barnes J.A., 1986, STAT TABLES SCI ENG, V3rd
[5] CATLETT J, 1991, EUROPEAN WORKING SES
[6] Huan Liu, 1996, Machine Learning. Proceedings of the Thirteenth International Conference (ICML '96), P319
[7] Kira K., 1992, P 10 NAT C ART INT
[8] LIU H, 1993, P 1 AUSTR NZ C INT I
[9] QUINLAN JR, 1993, C4 5 PROGR MACH LEAR
[10] Ragavan H., 1993, P 10 INT C MACH LEAR, P252

← 1 2 →