Proposal of Dominance-Based Rough Set Approach by STRIM and Its Applied Example
Proposal of Dominance-Based Rough Set Approach by STRIM and Its Applied Example
复制标题
STRIM基于优势的粗糙集方法的提出及其应用实例
DOI：
10.1007/978-3-319-60837-2_35
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
T. Saeki
中科院分区：
文献类型：
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作者：
Y. Kato;Takahiro Itsuno;T. Saeki
传统的粗糙集理论用于归纳隐藏在决策表数据集背后的if-then规则，决策表数据集包含一些条件属性和一个决策属性。原则上，每个属性都被视为一个名义量表。传统的粗糙集理论还扩展了其方法，以适用于表与顺序规模，这是用于评价用户的偏好，并提出了一个基于优势的粗糙集方法（DRSA）的传统规则归纳方法。本文还提出了一个DRSA的DRSA的DRSA的DRSA的DOMLEM与一致性指标的优势，将其应用到一个现实世界的问卷调查数据集，并通过比较与传统的方法DOMLEM的DOMLEM的有效性。
The conventional rough sets theory is used for inducing if-then rules hidden behind a dataset called the decision table which has some condition attributes and a decision attribute. Each attribute is considered in principle as a nominal scale. The conventional rough sets theory also extends its method in order to apply to the table with an ordinal scale which is used for rating the preference of users, and proposes a dominance-based rough set approach (DRSA) for the conventional rule induction methods. This paper also proposes a DRSA by STRIM named DOMSTRIM with a consistency index of dominance, applies it to a real-world dataset of a questionnaire survey and confirms the usefulness of DOMSTRIM by comparing with the conventional method DOMLEM.