A Classification Algorithm based on an Association Rule of Multiple Frequent Item-sets

被引：0

作者：

Liang, ZhiHeng ^{[1
]}

机构：

[1] Shenyang Normal Univ, Software Coll, Shenyang, Peoples R China

来源：

HIS 2009: 2009 NINTH INTERNATIONAL CONFERENCE ON HYBRID INTELLIGENT SYSTEMS, VOL 3, PROCEEDINGS | 2009年

关键词：

Data mining; ARMFI; Frequent Item-sets; Frequent Regions; Classification;

D O I：

10.1109/HIS.2009.271

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is necessary to discrete datasets firstly if you want to data mining an association rule of datasets consisting of many categorical and numeric attributes by a traditional algorithm. However, in view of the versatility, the applications of the traditional algorithm are limited. This paper propose a new algorithm called ARMFI(Association Role of Multiple Frequent Item-sets) which can data mining an Association Rule from datasets consisting of many categorical and numeric attributes directly and completely, and overcome disadvantage of the traditional algorithm. The result has been proofed that the ARMFI shows better performances than the traditional algorithm.

引用

页码：278 / 282

页数：5