Stable rule extraction and decision making in rough non-deterministic information analysis

Authors:
Hiroshi Sakai;Hitomi Okuma;Michinori Nakata;Dominik Ślȩzak
Affiliations:
(Correspd. E-mail: sakai@mns.kyutech.ac.jp) Mathematical Sciences Section, Department of Basic Sciences, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804, Japan;Faculty of Education and Welfare Science, Oita University, Dannoharu, Oita 870, Japan;Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba 283, Japan;Institute of Mathematics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland and Infobright Inc., Poland, Krzywickiego 34 pok. 219, 02-078 Warsaw, Poland
Venue:
International Journal of Hybrid Intelligent Systems - Rough and Fuzzy Methods for Data Mining
Year:
2011

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Abstract

Rough Non-deterministic Information Analysis (RNIA) is a rough set-based data analysis framework for Non-deterministic Information Systems (NISs). RNIA-related algorithms and software tools developed so far for rule generation provide good characteristics of NISs and can be successfully applied to decision making based on non-deterministic data. In this paper, we extend RNIA by introducing stability factor that enables to evaluate rules in a more flexible way and by developing a question-answering functionality that enables decision makers to analyze data gathered in NISs in case there are no pre-extracted rules that may address specified conditions.