Yoriaki Murata

Subspace-Based Decision Tree Retraining

2025

In this study, we propose a method for generating additional learning samples using subspaces to enhance the discriminative performance of Decision Trees. Although Decision Trees are known for their high interpretability as classifiers, they are …