Title
Incremental updating approximations for double-quantitative decision-theoretic rough sets with the variation of objects
Abstract
Double-quantitative decision-theoretic rough sets (Dq-DTRS) provide more comprehensive description methods for rough approximations of concepts, which lay foundations for the development of attribute reduction and rule extraction of rough sets. Existing researches on concept approximations of Dq-DTRS pay more attention to the equivalence class of each object in approximating a concept, and calculate concept approximations from the whole data set in a batch. This makes the calculation of approximations time consuming in dynamic data sets. In this paper, we first analyze the variations of equivalence classes, decision classes, conditional probability, internal grade and external grade in dynamic data sets while objects vary sequentially or simultaneously over time. Then we propose the updating mechanisms for the concept approximations of two types of Dq-DTRS models from incremental perspective in dynamic decision information systems with the sequential and batch variations of objects. Meanwhile, we design incremental sequential insertion, sequential deletion, batch insertion, batch deletion algorithms for two Dq-DTRS models. Finally, we present experimental comparisons showing the feasibility and efficiency of the proposed incremental approaches in calculating approximations and the stability of the incremental updating algorithms from the perspective of the runtime under different inserting and deleting ratios and parameter values.
Year
DOI
Venue
2020
10.1016/j.knosys.2019.105082
Knowledge-Based Systems
Keywords
Field
DocType
Double-quantitative decision-theoretic rough sets,Concept approximations,Incremental learning
Information system,Decision-theoretic rough sets,Data mining,Conditional probability,Computer science,Algorithm,Approximations of π,Rough set,Dynamic data,Equivalence class
Journal
Volume
ISSN
Citations 
189
0950-7051
3
PageRank 
References 
Authors
0.36
0
7
Name
Order
Citations
PageRank
Yanting Guo1624.38
E. C. C. Tsang21758.39
Meng Hu392.21
Xuxin Lin440.71
Degang Chen530.36
Weihua Xu6141.79
Binbin Sang7376.26