New measures of uncertainty for an interval-valued information system

被引：65
作者：
Xie, Ningxin [1 ]
Liu, Meng [2 ]
Li, Zhaowen [3 ]
Zhang, Gangqiang [4 ]
机构：
[1] Guangxi Univ Nationalities, Sch Software & Informat Secur, Nanning 530006, Guangxi, Peoples R China
[2] Guangxi Univ Nationalities, Sch Sci, Nanning 530006, Guangxi, Peoples R China
[3] Yulin Normal Univ, Key Lab Complex Syst Optimizat & Big Data Proc De, Yulin 537000, Guangxi, Peoples R China
[4] Guangxi Univ Nationalities, Sch Software & Informat Secur, Nanning 530006, Guangxi, Peoples R China
来源：
INFORMATION SCIENCES | 2019年 / 470卷
基金：
中国国家自然科学基金;
关键词：
Interval-valued information system; Rough set theory; Information granule; Information structure; Dependence; Measure; Uncertainty; Effectiveness; KNOWLEDGE GRANULATION; GRANULARITY MEASURES; ENTROPY MEASURES; GRANULES;
D O I：
10.1016/j.ins.2018.08.047
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An information system as a database that represents relationships between objects and attributes is an important mathematical model. An interval-valued information system is a generalized model of single-valued information systems. As important evaluation tools in the field of machine learning, measures of uncertainty can quantify the dependence and similarity between two targets. However, the existing measures of uncertainty for interval valued information systems have not been thoroughly researched. This paper is devoted to the study of new measures of uncertainty for an interval-valued information system. Information structures are first introduced in a given interval-valued information system. Then, the dependence between two information structures is depicted. Next, new measures of uncertainty for an interval-valued information system are investigated by using the information structures. As an application of the proposed measures, the rough entropy of a rough set is proposed by means of information granulation. Finally, a numerical experiment on the Face recognition dataset is presented to demonstrate the feasibility of the proposed measures, and a statistical effectiveness analysis is conducted. The results are helpful for understanding the essence of uncertainty in interval-valued information systems. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码：156 / 174
页数：19
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