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A New Decision Tree Algorithm Based on Rough Set and Entity Relationship  

Han, Sang-Wook (Department of Industrial Engineering, Hanyang University)
Kim, Jae-Yearn (Department of Industrial Engineering, Hanyang University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.33, no.2, 2007 , pp. 183-190 More about this Journal
Abstract
We present a new decision tree classification algorithm using rough set theory that can induce classification rules, the construction of which is based on core attributes and relationship between objects. Although decision trees have been widely used in machine learning and artificial intelligence, little research has focused on improving classification quality. We propose a new decision tree construction algorithm that can be simplified and provides an improved classification quality. We also compare the new algorithm with the ID3 algorithm in terms of the number of rules.
Keywords
Decision rules; Attribute Core; Discernibility Matrix; Rough Set theory;
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