Open AccessInformation measure of absolute and relative quantification in double‐quantitative decision‐theoretic rough set model
Author(s) -
Li Wentao,
Pedrycz Witold,
Xue Xiaoping,
Zhang Xiaoyan,
Fan Bingjiao,
Long Binghan
Publication year - 2018
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8315
Subject(s) - measure (data warehouse) , rough set , mathematics , absolute (philosophy) , set (abstract data type) , computer science , statistics , data mining , philosophy , epistemology , programming language
The absolute and relative quantifications between the equivalence class and the target concept are the two important research endeavours in rough set theory. Double‐quantitative decision‐theoretic rough set (Dq‐DTRS) models utilise both absolute quantification and relative quantification in their upper and lower approximations to reflect the distinctive degrees of quantitative information. Herein, the authors apply the information theory to Dq‐DTRS model to characterise and measure these two types of quantitative information. The expressions of the information entropy with regard to the two quantifications and their corresponding information co‐entropy are presented in DqI‐DTRS model and DqII‐DTRSmodel, respectively. This work makes a further study of Dq‐DTRS models by discussing the information measures with respect to absolute and relative quantification.