Positive Feature Values Prioritized Hierarchical Redundancy Eliminated Tree Augmented Naïve Bayes Classifier for Hierarchical Feature Spaces

The Hierarchical Redundancy Eliminated Tree Augmented Naïve Bayes (HRE-TAN) classifier is a semi-naïve Bayesian model that learns a type of hierarchical redundancy-free tree-like feature representation to estimate data distributions. In this work, we propose two new types of positive feature values prioritized hierarchical redundancy eliminated tree augmented naïve Bayes classifiers that focus on features bearing positive instance values. The two newly proposed methods are applied to 28 real-world bioinformatics datasets showing better predictive performance than the conventional HRE-TAN classifier.