Identifying the Most Explainable Classifier

18 October 2019

Papers citing "Identifying the Most Explainable Classifier"

7 / 7 papers shown

Title
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 58 198 0 22 Jul 2019
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 93 1,857 0 31 May 2018
Local Rule-Based Explanations of Black Box Decision Systems Riccardo Guidotti A. Monreale Salvatore Ruggieri D. Pedreschi Franco Turini F. Giannotti 128 437 0 28 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 124 3,961 0 06 Feb 2018
Programs as Black-Box Explanations Sameer Singh Marco Tulio Ribeiro Carlos Guestrin FAtt 62 55 0 22 Nov 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,976 0 16 Feb 2016
Methods and Models for Interpretable Linear Classification Berk Ustun Cynthia Rudin 89 44 0 16 May 2014