Rule-based Functionality for Decision Making with Reasoning and Its Application: Case Studies on Three Data Sets

By : Hiroshi Sakai, Zhiwen Jian, Touhid Mohammad Hossain, Junzo Watada

Page No: 157-173

Abstract:
We have been coping with rough set-based rule generation and Apriori-based rule generation. We developed a software tool termed “NIS-Apriori.” The software tool makes use of the characteristics of both rough sets and the Apriori algorithm. This NIS-Apriori generates certain rules and possible rules based on the possible world semantics, and the mathematical properties of “soundness and completeness” for defined rules are preserved. Some important propositions have been proved for the framework of the NIS-Apriori. We are now applying this environment to several different data sets, and we especially describe three cases of data sets in this paper. This paper newly considers the rule-based functionality for decision making with reasoning, which will recover the black-box problem in recent AI.

Authors :
Hiroshi Sakai
Department of Basic Sciences, Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804-8550, Japan.

Zhiwen Jian
Department of Basic Sciences, Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804-8550, Japan.

Touhid Mohammad Hossain
Computer & Information Sciences Department,  Faculty of Science and Information Technology,  Universiti Teknologi PETRONAS,  Seri Iskandar, Perak Darul Ridzuan 32610, Malaysia.

Junzo Watada
Computer & Information Sciences Department,  Faculty of Science and Information Technology,  Universiti Teknologi PETRONAS,  Seri Iskandar, Perak Darul Ridzuan 32610, Malaysia.
 

DOI: https://doi.org/10.32381/JCISS.2020.45.1-4.2