Regularized impurity reduction: Accurate decision trees with complexity guarantees

23 August 2022

Papers citing "Regularized impurity reduction: Accurate decision trees with complexity guarantees"

10 / 10 papers shown

Title
Top-down induction of decision trees: rigorous guarantees and inherent limitations Guy Blanc Jane Lange Li-Yang Tan 45 25 0 18 Nov 2019
On the Optimality of Trees Generated by ID3 Alon Brutzkus Amit Daniely Eran Malach 41 10 0 11 Jul 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,813 0 28 Feb 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016
On the boosting ability of top-down decision tree learning algorithm for multiclass classification A. Choromańska K. Choromanski Mariusz Bojarski 45 7 0 17 May 2016
Scenario Submodular Cover Nathaniel Grammel L. Hellerstein Devorah Kletenik P. Lin 52 80 0 10 Mar 2016
OpenML: networked science in machine learning Joaquin Vanschoren Jan N. van Rijn B. Bischl Luís Torgo FedML AI4CE 163 1,327 0 29 Jul 2014
Near-Optimal Bayesian Active Learning with Noisy Observations Daniel Golovin Andreas Krause Debajyoti Ray 115 206 0 15 Oct 2010
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization Daniel Golovin Andreas Krause 145 603 0 21 Mar 2010
Average-Case Active Learning with Costs Andrew Guillory J. Bilmes VLM FedML 89 48 0 18 May 2009