Authors: HaiJun Li, LiMin Wang, Ling Li, SenMiao Yuan
Tags: 2004, conceptual modeling
In this paper, a hybrid learning approach named Flexible NBTree is proposed. Flexible NBTree uses Bayes measure δ to select proper test and applies post-discretization strategy to construct decision tree. The finial decision tree nodes contain univariate splits as regular decision trees, but the leaf nodes contain General Naive Bayes, which is a variant of standard Naive Bayesian classifier. Empirical studies on a set of natural domains show that Flexible NBTree has clear advantages with respect to the generalization ability when compared against its counterpart, NBTree.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-540-30464-7_26
