JACIII Vol.20 No.5 pp. 712-720
doi: 10.20965/jaciii.2016.p0712


Rough-Set-Based Interrelationship Mining for Incomplete Decision Tables

Yasuo Kudo* and Tetsuya Murai**

*College of Information and Systems, Graduate School of Engineering, Muroran Institute of Technology
27-1 Mizumoto, Muroran 050-8585, Japan

**Faculty of Science and Technology, Chitose Institute of Science and Technology
758-65 Bibi, Chitose 066-8655, Japan

February 3, 2016
June 1, 2016
September 20, 2016
interrelationship mining, incomplete decision tables, rough set, similarity relation
Rough-set-based interrelationship mining enables to extract characteristics by comparing the values of the same object between different attributes. To apply this interrelationship mining to incomplete decision tables with null values, in this study, we discuss the treatment of null values in interrelationships between attributes. We introduce three types of null values for interrelated condition attributes and formulate a similarity relation by such attributes with these null values.
Cite this article as:
Y. Kudo and T. Murai, “Rough-Set-Based Interrelationship Mining for Incomplete Decision Tables,” J. Adv. Comput. Intell. Intell. Inform., Vol.20 No.5, pp. 712-720, 2016.
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Last updated on May. 10, 2024