SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator

7 August 2023

Papers citing "SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator"

10 / 10 papers shown

Title
SurvNAM: The machine learning survival model explanation Lev V. Utkin Egor D. Satyukov A. Konstantinov AAML FAtt 48 29 0 18 Apr 2021
Benchmarking and Survey of Explanation Methods for Black Box Models F. Bodria F. Giannotti Riccardo Guidotti Francesca Naretto D. Pedreschi S. Rinzivillo XAI 86 224 0 25 Feb 2021
How Interpretable and Trustworthy are GAMs? C. Chang S. Tan Benjamin J. Lengerich Anna Goldenberg R. Caruana FAtt 87 77 0 11 Jun 2020
Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal Levi Melnick Nicholas Frosst Xuezhou Zhang Ben Lengerich R. Caruana Geoffrey E. Hinton 62 412 0 29 Apr 2020
SurvLIME: A method for explaining machine learning survival models M. Kovalev Lev V. Utkin E. Kasimov 203 90 0 18 Mar 2020
Explaining the Explainer: A First Theoretical Analysis of LIME Damien Garreau U. V. Luxburg FAtt 40 175 0 10 Jan 2020
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 101 3,922 0 06 Feb 2018
DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network Jared Katzman Uri Shaham Jonathan Bates A. Cloninger Tingting Jiang Y. Kluger BDL CML OOD 330 1,243 0 02 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 746 16,828 0 16 Feb 2016
On the use of Harrell's C for clinical risk prediction via random survival forests M. Schmid Marvin N. Wright A. Ziegler 64 96 0 11 Jul 2015