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Found 3 papers, 1 papers with code
Loss-Optimal Classification Trees: A Generalized Framework and the Logistic Case
The Classification Tree (CT) is one of the most common models in interpretable machine learning.
A Novel Memetic Strategy for Optimized Learning of Classification Trees
Given the increasing interest in interpretable machine learning, classification trees have again attracted the attention of the scientific community because of their glass-box structure.
Contextual Decision Trees
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.
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