Applying Rough Sets to Data Tables Containing Missing Values

Authors:
Michinori Nakata;Hiroshi Sakai
Affiliations:
Faculty of Management and Information Science, Josai International University, 1 Gumyo, Togane, Chiba, 283-8555, Japan;Department of Mathematics and Computer Aided Sciences, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, 804-8550, Japan
Venue:
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Year:
2007

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Applying Rough Sets to Data Tables Containing Missing Values

RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms

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Abstract

Rough sets are applied to data tables containing missing values. Discernibility and indiscernibility between a missing value and another value are considered simultaneously. A family of possible equivalence classes is obtained, in which each equivalence class has the possibility that it is an actual one. By using the family of possible equivalence classes, we can derive lower and upper approximations, even if the approximations are not obtained by previous methods.Furthermore, the lower and upper approximations coincide with those obtained from methods of possible worlds.