Experiments prove that the tree size and classification accuracy of the decision trees generated by the improved algorithm is superior to the ID3 algorithm.
A Study on Decision Tree Induction (ID3) based on Bayesian Decision Theoretic Rough Set ... Decision tree algorithms are widely used for data classification and ...
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An Algorithm for Constructing Decision Tree Based on Variable Precision Rough Set Model · Computer Science, Mathematics. 2008 Fourth International Conference on ...
A novel method for inducing ID3 decision trees based on variable precision rough set ... Classification is the main research target of many algorithms in data ...
This paper proposes a decision tree generation method based on variable precision rough set theory. The proposed method mainly deals with the uncertain.
Jul 13, 2023 · In order to solve the above problems, we propose an improved ID3 algorithm (called DIGGI) based on variable precision neighborhood rough sets.
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Third, a variable precision neighborhood rough set model is constructed using the new similarities, and a novel decision tree algorithm is proposed based on ...
Abstract-In this paper, an optimize and effective algorithm is proposed for constructing decision tree based on variable precision rough set theory which ...
... based on rough set ... approach is better in selecting nodes for inducing decision trees than ID3. ... This paper presents a novel rough set method for ...
Rough Set theory (RS) simplifies the search for dominant attributes in the information systems. In this paper, Rough set based Decision Tree (RDT) model ...
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