A Weighted Fuzzy Rough Sets based Approach for Rule Extraction

被引：0
|
作者：
Hsiao, Chih-Ching [1 ]
Chuang, Chen-Chia [2 ]
Jeng, Jin-Tsong [3 ]
Su, Shun-Feng [4 ]
机构：
[1] Kao Yuan Univ, Dept Informat Technol, Kaohsiung, Taiwan
[2] Natl Ilan Univ, Dept Elect Engn, Ilan, Taiwan
[3] Natl Formosa Univ, Dept Comp Sci & Informat, Yunlin, Taiwan
[4] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei, Taiwan
来源：
2013 PROCEEDINGS OF SICE ANNUAL CONFERENCE (SICE) | 2013年
关键词：
ATTRIBUTE REDUCTION; FEATURE-SELECTION; CLASSIFICATION; APPROXIMATION; ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Rough sets approach of attributes reduction can be used as a purely structural method for reducing dimensionality using information contained within the dataset and preserving the meaning of the features. In this paper, the weighted interval-value fuzzy-rough attribute reduction algorithm is proposed for interval-value data. It will introduce IT2 into hybrid fuzzy-rough QuickReduct algorithm to deal with interval-value data. The "weighted" concept is not only enhancing prior knowledge, and also reduces unknown information effect.
引用
收藏
页码：104 / 109
页数：6
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