An evaluation of approaches to classification rule selection

被引：18

作者：

Coenen, F ^{[1
]}

Leng, P ^{[1
]}

机构：

[1] Univ Liverpool, Dept Comp Sci, Liverpool L69 3BX, Merseyside, England

来源：

FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS | 2004年

关键词：

D O I：

10.1109/ICDM.2004.10012

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper a number of Classification Rule evaluation measures are considered. In particular the authors review the use of a variety of selection techniques used to order classification rules contained in a classifier and a number of mechanisms used to classify unseen data. The authors demonstrate that rule ordering founded on the size of antecedent works well given certain conditions.

引用

页码：359 / 362

页数：4

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