RoughTree A Classifier with Naive-Bayes and Rough Sets Hybrid in Decision Tree Representation

@article{Ji2007RoughTreeAC,
  title={RoughTree A Classifier with Naive-Bayes and Rough Sets Hybrid in Decision Tree Representation},
  author={Yangsheng Ji and Lin Shang},
  journal={2007 IEEE International Conference on Granular Computing (GRC 2007)},
  year={2007},
  pages={221-221}
}
This paper presents a semi-naive classifier named RoughTree, which is designed to alleviate the attribute interdependence problem of Naive Bayesian classifier. RoughTree uses the attribute dependence detecting measure in rough sets and splits the dataset into subspaces according to the selected attributes, which hold the maximum values by the attribute dependence measure. This process continues the same way a decision tree splits until the stopping criterion is satisfied. Then, the result is a… CONTINUE READING

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