重庆邮电大学学报（自然科学版）2008，Vol.20Issue(3)：254-265,12.
Rough sets: the classical and extended views
Rough sets: the classical and extended views
ZIARKO Wojciech1
作者信息
- 1. Department of Computer Science,University of Regina,SK A4S 0A2, Canada
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摘要
Abstract
The article is a comprehensive review of two major approaches to rough set theory: the classic rough setmodel introduced by Pawlak and the probabilistic approaches. The classic model is presented as a staging ground to the discussion of two varieties of the probabilistic approach, i.e. of the variable precision and Bayesian rough set models. Both of these models extend the classic model to deal with stochastic interactions while preserving the basicideas of the original rough set theory, such as set approximations, data dependencies, reducts etc. The probabilistic models are able to handle weaker data interactions than the classic model, thus extending the applicability of the rough set paradigm. The extended models are presented in considerable detail with some illustrative examples.关键词
rough sets/ variable precision rough sets/ Bayesian rough sets/data dependencies/ probabilistic rough setsKey words
rough sets/ variable precision rough sets/ Bayesian rough sets/data dependencies/ probabilistic rough sets分类
信息技术与安全科学引用本文复制引用
ZIARKO Wojciech..Rough sets: the classical and extended views[J].重庆邮电大学学报（自然科学版）,2008,20(3):254-265,12.
