Research and Implement of Classification Rule Mining Algorithm Based on Attribute Reduction
This paper brings up a new classification algorithm of data mining (CRMA) in any scale relation database. Based on Rough set theory it divides relation table into several equivalence class based on attribute values, calculates information capacity in decision factor of the every condition attribution, eliminates redundancy attributions, and erases repeat units. Then classification rules can be obtained through strong equivalence class which relation table was reduced. It overcomes the redundancy nature, complicated nature and unfit nature to big capacity data or increment data of some classification algorithm at present. It has higher efficiency and widespread application perspective in large and incremental databases. The mining algorithm and an example are discussed in details.
Attribute reduction Classification rule Data mining Condition attribute Decision-making attribute
Shiqun Yin Yuhui Qiu Chengwen Zhong Jifu Zhou
Faculty of Computer and Information Science Southwest University Chongqing, China 400715 Center for High Performance Computing Northwestern Polytechnical University Xian, China 710072
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）