Compared with the Pawlak rough set model, decision-theoretic rough set (DTRS) models
have relatively powerful data processing capability for complex and low quality data …

Feature selection plays an important role as a preprocessing step for pattern recognition and
machine learning. The goal of feature selection is to determine an optimal subset of relevant …

从三支决策3 个历史发展阶段出发, 通过粗糙集和粒计算两个研究视角对三支决策的发展踪迹和
演化过程进行介绍. 分析了三支决策与粗糙集理论的历史脉络, 内在联系和相互关系 …

In the previous decision-theoretic rough sets (DTRS), its loss function values are precise.
This paper extends the precise values of loss functions to a more realistic stochastic …

从三支决策发展历史和已有研究出发, 在总结和分析三支决策近年来理论, 方法,
算法及应用的基础上, 基于时间和空间两个维度, 分别提出了时间三支决策模型和空间三支决策 …

Three-way decisions for classification consist of the actions of acceptance, rejection and non-
commitment (ie, neither acceptance nor rejection) in deciding whether an object is in a class …

A relation is viewed as a granularity from a granular computing perspective. A classic rough
set contains only one granularity. A multi-granulation rough set contains multiple …

This paper defines an improved similarity degree based on inclusion degree as well as
advanced information system based on interval coverage and credibility, and thus an …

In 1982, Pawlak proposed a theory of rough sets for data analysis. A fundamental concept of
rough sets is the approximation of a set by a pair of lower and upper approximations or three …