A novel approach to predictive analysis using attribute-oriented rough fuzzy sets

作者：

Highlights：

• With data mining’s point of view, we propose a novel rough fuzzy sets of fuzzy information systems.

• Based on δ-clusters, (γ, δ)-rough fuzzy sets inherit the ability that predict it with growth trend.

• We use (γ, δ)-rough fuzzy set theory to predictive analysis.

• The randomness of the algorithm is analyzed.

摘要

•With data mining’s point of view, we propose a novel rough fuzzy sets of fuzzy information systems.•Based on δ-clusters, (γ, δ)-rough fuzzy sets inherit the ability that predict it with growth trend.•We use (γ, δ)-rough fuzzy set theory to predictive analysis.•The randomness of the algorithm is analyzed.

论文关键词：Fuzzy information system (FIS),δ-Cluster,(γ, δ)-Rough fuzzy set ((γ, δ)-RFS),TPELDTP,Decision making

论文评审过程：Received 18 October 2019, Revised 10 January 2020, Accepted 6 June 2020, Available online 18 June 2020, Version of Record 21 July 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113644