Abstract
Decision tree techniques have been widely used to build classification models. In this study, we attempted to increase the prediction accuracy of a decision tree model by integrating local application of Naive Bayes classifier. We performed a large-scale comparison with other state-of-the-art algorithms on 30 standard benchmark datasets and the proposed method gave statistical better accuracy in some cases.
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