Decision-theoretic rough sets under dynamic granulation

Sang, Yanli; Liang, Jiye; Qian, Yuhua

doi:10.1016/j.knosys.2015.08.001

Cited by 50 publications

(6 citation statements)

References 50 publications

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“…Granules may be understood as groups, classes, or clusters of elements, which are drawn together by indistinguishability, similarity, proximity, or functionality [61] . Granular computing (GrC), serving as an effective tool of complex problem solving, massive dataset mining and fuzzy information processing, has become a very active field of research in recent years [1,2,20,29,31,35,39,40,43,44,48,51,[54][55][56][57][58][59] .…”

Section: Introductionmentioning

confidence: 99%

A new approach of optimal scale selection to multi-scale decision tables

2017

Information Sciences

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Section: Introductionmentioning

confidence: 99%

A new approach of optimal scale selection to multi-scale decision tables

2017

Information Sciences

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“…In Decision-theoretic rough sets, S = {C, ¬C} {P, N} is supposed to be two states that the object belongs to or belongs to C or¬C [1,2,37]. In addition, the set of actions is represented by A = {a P , a B , a N }, where a P , a B , and a N indicate three decision actions for classifying an object, which correspond to x ∈ POS(C), x ∈ NEG(C), and x ∈ BND(C) in the decision-making process.…”

Section: Decision-theoretic Rough Setsmentioning

confidence: 99%

Approaches to Three-Way Decisions Based on the Evaluation of Probabilistic Linguistic Terms Sets

Liu

Zhou

2021

Symmetry

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The method of determining probability thresholds of three-way decisions (3WDs) has always been the key of research, especially in the current environment with a large number of data and uncertainties. Among these problems, there will be correlation and similarity between them. In the light of these problems, the loss function with Probabilistic Linguistic Terms Sets (PLTSs) is introduced in the paper, and then we propose a PLTS evaluation-based approach to determine the thresholds and derive 3WDs. According to the definition and characters of PLTSs, the PLTSs loss function matrix is constructed firstly. Then using the equivalent model of Decision-theoretic rough sets (DTRSs), we construct the equivalent model (i.e., the αopt-model and the βopt-model, which are symmtrical) and try to find the optimal solution to determine the thresholds. Based on that, we propose a novel three-way decision approach under PLTSs evaluations. Finally, the validity of the method is verified by an example.

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“…The non-monotonicity brings a difficulty to attribute reduction for sequential three-way decision-making [43]. This…”

Section: Attribute Reduction For Sequential Three-way Decisions Undermentioning

confidence: 99%

Attribute reduction for sequential three-way decisions under dynamic granulation

Jin

Dang

Yue

et al. 2017

International Journal of Approximate Reasoning

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In real-world decision making, sequential three-way decisions are an effective way of human problem solving under multiple levels of granularity. Making the right decision at the most optimal level is a crucial issue. To this end, we address the attribute reduction problem for sequential three-way decisions under dynamic granulation. By reviewing the existing definitions of attribute reducts, a new attribute reduct for sequential three-way decisions is defined, and a corresponding monotonic attribute significance measure is designed. An attribute reduction algorithm satisfying the monotonicity of the probabilistic positive region is developed. The relationships of the different attribute reducts, the probabilistic positive regions and the probabilistic positive rules for decision-theoretic rough set models are further discussed under global view, local view and sequential three-way decisions. Experimental results demonstrate that our method is effective. This study will provide a new insight into the attribute reduction problem of sequential three-way decisions.

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Decision-theoretic rough sets under dynamic granulation

Cited by 50 publications

References 50 publications

A new approach of optimal scale selection to multi-scale decision tables

A new approach of optimal scale selection to multi-scale decision tables

Approaches to Three-Way Decisions Based on the Evaluation of Probabilistic Linguistic Terms Sets

Attribute reduction for sequential three-way decisions under dynamic granulation

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