Incremental Three-Way Decisions with Incomplete Information

The theory of rough sets proposed a framework for approximating concepts by three pair-wise disjoint regions, namely, the positive, boundary and negative regions. Rules generated by the three regions form three-way decision rules, which are acceptance, deferment and rejection decisions. The periodic...

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Bibliographic Details
Published inRough Sets and Current Trends in Computing pp. 128 - 135
Main Authors Luo, Chuan, Li, Tianrui
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2014
SeriesLecture Notes in Computer Science
Subjects
incomplete decision system
incremental updating
three-way decisions
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ISBN331908643X
9783319086439
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-08644-6_13

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Summary:The theory of rough sets proposed a framework for approximating concepts by three pair-wise disjoint regions, namely, the positive, boundary and negative regions. Rules generated by the three regions form three-way decision rules, which are acceptance, deferment and rejection decisions. The periodic updating of decision rules is required due to the dynamic nature of decision systems. Incremental learning technique is an effective way to solve the problem of dynamic data, which is capable of updating the learning results incrementally without recalculation in the total data set from scratch. In this paper, we present a methodology for incremental updating three-way decisions with incomplete information when the object set varies through the time.
ISBN:331908643X
9783319086439
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-08644-6_13