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cs.LG2024★ 1 cited
Robust Loss Functions for Training Decision Trees with Noisy Labels
Jonathan Wilton, Nan Ye
We consider training decision trees using noisily labeled data, focusing on loss functions that can lead to robust learning algorithms. Our contributions are threefold. First, we o…
cs.LG2022★ 9 cited
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization
Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko +2
The need to learn from positive and unlabeled data, or PU learning, arises in many applications and has attracted increasing interest. While random forests are known to perform wel…