全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Reduction Algorithms Based on Discernibility Matrix: The Ordered Attributes Method
Constraint-Preserving Architecture Transformations:A Graph Rewriting Appraoch

Keywords: rough set theory,principle of discernibility matrix,inductive machine learning

Full-Text   Cite this paper   Add to My Lib

Abstract:

In this paper, we present reduction algorithms based on the principle of Skowron's discernibility matrix - the ordered attributes method. The completeness of the algorithms for Pawlak reduct and the uniqueness for a given order of the attributes are proved. Since a discernibility matrix requires the size of the memory of U2, U is a universe of objects, it would be impossible to apply these algorithms directly to a massive object set. In order to solve the problem, a so-called quasi-discernibility matrix and two reduction algorithms are proposed. Although the proposed algorithms are incomplete for Pawlak reduct, their opimal paradigms ensure the completeness as long as they satisfy some conditions. Finally we consider the problem on the reduction of distributive object sets.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133