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On Tackling Explanation Redundancy in Decision Trees

On Tackling Explanation Redundancy in Decision Trees

20 May 2022
Yacine Izza
Alexey Ignatiev
João Marques-Silva
    FAtt
ArXivPDFHTML

Papers citing "On Tackling Explanation Redundancy in Decision Trees"

5 / 5 papers shown
Title
Finding Minimum-Cost Explanations for Predictions made by Tree Ensembles
Finding Minimum-Cost Explanations for Predictions made by Tree Ensembles
John Törnblom
Emil Karlsson
Simin Nadjm-Tehrani
FAtt
49
0
0
16 Mar 2023
Feature Necessity & Relevancy in ML Classifier Explanations
Feature Necessity & Relevancy in ML Classifier Explanations
Xuanxiang Huang
Martin C. Cooper
António Morgado
Jordi Planes
João Marques-Silva
FAtt
20
17
0
27 Oct 2022
Model Interpretability through the Lens of Computational Complexity
Model Interpretability through the Lens of Computational Complexity
Pablo Barceló
Mikaël Monet
Jorge A. Pérez
Bernardo Subercaseaux
114
93
0
23 Oct 2020
Personalized Treatment for Coronary Artery Disease Patients: A Machine
  Learning Approach
Personalized Treatment for Coronary Artery Disease Patients: A Machine Learning Approach
Dimitris Bertsimas
Agni Orfanoudaki
R. Weiner
45
38
0
18 Oct 2019
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,231
0
24 Jun 2017
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