On rule interestingness measures

被引：127

作者：

Freitas, AA ^{[1
]}

机构：

[1] Fed Ctr Technol Educ, CEFET, PR, DAINF, BR-80230901 Curitiba, Parana, Brazil

来源：

KNOWLEDGE-BASED SYSTEMS | 1999年 / 12卷 / 5-6期

关键词：

data mining; rule interestingness; rule surprisingness;

D O I：

10.1016/S0950-7051(99)00019-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper discusses several factors influencing the evaluation of the degree of interestingness of rules discovered by a data mining algorithm. This article aims at: (1) drawing attention to several factors related to rule interestingness that have been somewhat neglected in the literature; (2) showing some ways of modifying rule interestingness measures to take these factors into account; (3) introducing a new criterion to measure attribute surprisingness, as a factor influencing the interestingness of discovered rules. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：309 / 315

页数：7

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