Paper Info
Title
Parameter Selection and Uncertainty Measurement for Variable Precision Probabilistic Rough Set.
Abstract
In this paper, we consider the problem of parameter selection and uncertainty measurement for a variable precision probabilistic rough set. Firstly, within the framework of the variable precision probabilistic rough set model, the relative discernibility of a variable precision rough set in probabilistic approximation space is discussed, and the conditions that make precision parameters a discernible in a variable precision probabilistic rough set are put forward. Concurrently, we consider the lack of predictability of precision parameters in a variable precision probabilistic rough set, and we propose a systematic threshold selection method based on relative discernibility of sets, using the concept of relative discernibility in probabilistic approximation space. Furthermore, a numerical example is applied to test the validity of the proposed method in this paper. Secondly, we discuss the problem of uncertainty measurement for the variable precision probabilistic rough set. The concept of classical fuzzy entropy is introduced into probabilistic approximation space, and the uncertain information that comes from approximation space and the approximated objects is fully considered. Then, an axiomatic approach is established for uncertainty measurement in a variable precision probabilistic rough set, and several related interesting properties are also discussed. Thirdly, we study the attribute reduction for the variable precision probabilistic rough set. The definition of reduction and its characteristic theorems are given for the variable precision probabilistic rough set. The main contribution of this paper is twofold. One is to propose a method of parameter selection for a variable precision probabilistic rough set. Another is to present a new approach to measurement uncertainty and the method of attribute reduction for a variable precision probabilistic rough set.
Year
DOI
Venue
2018
10.4149/cai_2018_3_614
COMPUTING AND INFORMATICS
Keywords
Field
DocType
Rough set,probabilistic approximation space,relative discernibility,variable precision probabilistic rough set,approximation reduction
Computer science,Variable precision,Measurement uncertainty,Algorithm,Theoretical computer science,Rough set,Probabilistic logic
Journal
Volume
Issue
ISSN
37
3
1335-9150
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Weimin Ma142726.76
Yue Lei224.76
Bingzhen Sun369631.92
Haiyan Zhao4713.00