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Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach

29 June 2016

Papers citing "Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach"

34 / 34 papers shown

Title
Generating Global and Local Explanations for Tree-Ensemble Learning Methods by Answer Set Programming A. Takemura Katsumi Inoue 49 0 0 14 Oct 2024
Interpretable Responsibility Sharing as a Heuristic for Task and Motion Planning Arda Sarp Yenicesu Sepehr Nourmohammadi Berk Cicek Ozgur S. Oguz 100 0 0 09 Sep 2024
Minimising changes to audit when updating decision trees Anj Simmons Scott Barnett Anupam Chaudhuri Sankhya Singh Shangeetha Sivasothy 27 0 0 29 Aug 2024
A survey and taxonomy of methods interpreting random forest models Maissae Haddouchi A. Berrado 100 3 0 17 Jul 2024
Decision Predicate Graphs: Enhancing Interpretability in Tree Ensembles Leonardo Arrighi Luca Pennella G. Tavares Sylvio Barbon Junior 66 2 0 03 Apr 2024
Forest-ORE: Mining Optimal Rule Ensemble to interpret Random Forest models Haddouchi Maissae Berrado Abdelaziz 71 1 0 26 Mar 2024
Combination of Weak Learners eXplanations to Improve Random Forest eXplicability Robustness Riccardo Pala Esteban García-Cuesta 28 0 0 29 Feb 2024
Learning Interpretable Rules for Scalable Data Representation and Classification Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 56 8 0 22 Oct 2023
Explainable AI applications in the Medical Domain: a systematic review Nicoletta Prentzas A. Kakas Constantinos S. Pattichis 69 11 0 10 Aug 2023
HealthPrism: A Visual Analytics System for Exploring Children's Physical and Mental Health Profiles with Multimodal Data Zhihan Jiang Handi Chen Rui Zhou Jing Deng Xinchen Zhang Running Zhao Cong Xie Yifang Wang Edith C.H. Ngai 106 6 0 23 Jul 2023
Explaining with Greater Support: Weighted Column Sampling Optimization for q-Consistent Summary-Explanations Chen Peng Zhengqi Dai Guangping Xia Yajie Niu Yihui Lei 45 0 0 09 Feb 2023
Simplification of Forest Classifiers and Regressors Atsuyoshi Nakamura Kento Sakurada 55 1 0 14 Dec 2022
Local Multi-Label Explanations for Random Forest Nikolaos Mylonas Ioannis Mollas Nick Bassiliades Grigorios Tsoumakas FAtt 42 7 0 05 Jul 2022
TE2Rules: Explaining Tree Ensembles using Rules G. R. Lal Xiaotong Chen Varun Mithal 28 3 0 29 Jun 2022
Explainable Models via Compression of Tree Ensembles Siwen Yan Sriraam Natarajan Saket Joshi Roni Khardon Prasad Tadepalli 27 3 0 16 Jun 2022
HEX: Human-in-the-loop Explainability via Deep Reinforcement Learning Michael T. Lash 86 0 0 02 Jun 2022
Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making Oskar Wysocki J. Davies Markel Vigo Anne Caroline Armstrong Dónal Landers Rebecca Lee André Freitas 78 70 0 11 Apr 2022
BELLATREX: Building Explanations through a LocaLly AccuraTe Rule EXtractor Klest Dedja F. Nakano Konstantinos Pliakos C. Vens 56 5 0 29 Mar 2022
AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box David Dandolo Chiara Masiero Mattia Carletti Davide Dalle Pezze Gian Antonio Susto FAtt LRM 62 23 0 23 Dec 2021
Generating Explainable Rule Sets from Tree-Ensemble Learning Methods by Answer Set Programming A. Takemura Katsumi Inoue 41 7 0 17 Sep 2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms Martin Pawelczyk Sascha Bielawski J. V. D. Heuvel Tobias Richter Gjergji Kasneci CML 91 105 0 02 Aug 2021
Conclusive Local Interpretation Rules for Random Forests Ioannis Mollas Nick Bassiliades Grigorios Tsoumakas FaML FAtt 72 18 0 13 Apr 2021
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers Wei Huang Xingyu Zhao Xiaowei Huang AAML 59 11 0 16 Oct 2020
Explainability via Responsibility Faraz Khadivpour Matthew J. Guzdial 23 2 0 04 Oct 2020
Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning Yiming Li Jiawang Bai Jiawei Li Xue Yang Yong Jiang Shutao Xia 301 6 0 21 Aug 2020
Explainable Artificial Intelligence: a Systematic Review Giulia Vilone Luca Longo XAI 110 271 0 29 May 2020
Born-Again Tree Ensembles Thibaut Vidal Toni Pacheco Maximilian Schiffer 140 54 0 24 Mar 2020
LionForests: Local Interpretation of Random Forests Ioannis Mollas Nick Bassiliades I. Vlahavas Grigorios Tsoumakas 87 12 0 20 Nov 2019
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models Benjamin J. Lengerich S. Tan C. Chang Giles Hooker R. Caruana 79 42 0 12 Nov 2019
A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework Homayun Afrabandpey Tomi Peltola Juho Piironen Aki Vehtari Samuel Kaski 77 3 0 21 Oct 2019
Model Bridging: Connection between Simulation Model and Neural Network Keiichi Kisamori Keisuke Yamazaki Yuto Komori Hiroshi Tokieda 41 1 0 22 Jun 2019
Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness Jiawang Bai Yiming Li Jiawei Li Yong Jiang Shutao Xia 87 15 0 14 Mar 2019
Understanding Learned Models by Identifying Important Features at the Right Resolution Kyubin Lee Akshay Sood M. Craven 54 8 0 18 Nov 2018
Interpreting Tree Ensembles with inTrees Houtao Deng 126 248 0 23 Aug 2014