A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds

18 October 2021

Papers citing "A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds"

11 / 11 papers shown

Title
On the Convergence of CART under Sufficient Impurity Decrease Condition Rahul Mazumder Haoyue Wang 62 3 0 26 Oct 2023
MDI+: A Flexible Random Forest-Based Feature Importance Framework Abhineet Agarwal Ana M. Kenney Yan Shuo Tan Tiffany M. Tang Bin-Xia Yu 41 11 0 04 Jul 2023
From Shapley Values to Generalized Additive Models and back Sebastian Bordt U. V. Luxburg FAtt TDI 74 35 0 08 Sep 2022
An initial alignment between neural network and target is needed for gradient descent to learn Emmanuel Abbe Elisabetta Cornacchia Jan Hązła Christopher Marquis 24 16 0 25 Feb 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods Abhineet Agarwal Yan Shuo Tan Omer Ronen Chandan Singh Bin-Xia Yu 65 27 0 02 Feb 2022
Fast Interpretable Greedy-Tree Sums Yan Shuo Tan Chandan Singh Keyan Nasseri Abhineet Agarwal James Duncan Omer Ronen M. Epland Aaron E. Kornblith Bin-Xia Yu AI4CE 27 6 0 28 Jan 2022
Large Scale Prediction with Decision Trees Jason M. Klusowski Peter M. Tian 18 42 0 28 Apr 2021
Random Planted Forest: a directly interpretable tree ensemble M. Hiabu E. Mammen Josephine T. Meyer 10 5 0 29 Dec 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017
A Random Forest Guided Tour Gérard Biau Erwan Scornet AI4TS 143 2,725 0 18 Nov 2015
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Marvin N. Wright A. Ziegler 93 2,732 0 18 Aug 2015