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The branching structure of trees on directed sets (Combinatorial and Descriptive Set Theory)
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A Framework for a Decision Tree Learning Algorithm with Rough Set Theory
Communications in Computer and Information Science, 2015In this paper, we improve the conventional decision tree learning algorithm using rough set theory. First, our approach gets the upper approximate for each class. Next, it generates the decision tree from each upper approximate. Each decision tree shows whether the data item is in this class or not. Our approach classifies the unlabeled data item using
Jun Hakura, Hamido Fujita
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An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees
Fundamenta Informaticae, 2009Decision trees are one of the most popular data-mining techniques for knowledge discovery. Many approaches for induction of decision trees often deal with the continuous data and missing values in information systems. However, they do not perform well in real situations.
Jing Song, Tianrui Li 0001, Da Ruan 0001
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