3 papers
stat.ML2023
Loss-Optimal Classification Trees: A Generalized Framework and the Logistic Case
Tommaso Aldinucci, Matteo Lapucci
The Classification Tree (CT) is one of the most common models in interpretable machine learning. Although such models are usually built with greedy strategies, in recent years, tha…
cs.LG2023
A Novel Memetic Strategy for Optimized Learning of Classification Trees
Tommaso Aldinucci
Given the increasing interest in interpretable machine learning, classification trees have again attracted the attention of the scientific community because of their glass-box stru…
stat.ML2022
Contextual Decision Trees
Tommaso Aldinucci, Enrico Civitelli, Leonardo di Gangi +1
Focusing on Random Forests, we propose a multi-armed contextual bandit recommendation framework for feature-based selection of a single shallow tree of the learned ensemble. The tr…