Learning Certifiably Optimal Rule Lists for Categorical Data

Learning Certifiably Optimal Rule Lists for Categorical Data

6 April 2017

Nicholas Larus-Stone

Papers citing "Learning Certifiably Optimal Rule Lists for Categorical Data"

12 / 12 papers shown

Title
Efficient Exploration of the Rashomon Set of Rule Set Models Martino Ciaperoni Han Xiao A. Gionis 18 3 0 05 Jun 2024
Feature Importance Measurement based on Decision Tree Sampling Chao Huang Diptesh Das Koji Tsuda FAtt 16 2 0 25 Jul 2023
bsnsing: A decision tree induction method based on recursive optimal boolean rule composition Yan-ching Liu 20 6 0 30 May 2022
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies Riccardo Fogliato Alexandra Chouldechova Zachary Chase Lipton 16 31 0 03 Sep 2021
Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff Michael J. Naylor C. French Samantha R. Terker Uday Kamath 25 10 0 12 Jul 2021
Characterizing the risk of fairwashing Ulrich Aivodji Hiromi Arai Sébastien Gambs Satoshi Hara 12 26 0 14 Jun 2021
On Explaining Decision Trees Yacine Izza Alexey Ignatiev João Marques-Silva FAtt 16 83 0 21 Oct 2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction Caroline Linjun Wang Bin Han Bhrij Patel Cynthia Rudin FaML HAI 57 83 0 08 May 2020
Transparent Classification with Multilayer Logical Perceptrons and Random Binarization Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 11 29 0 10 Dec 2019
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model Tong Wang Qihang Lin 13 19 0 10 May 2019
VINE: Visualizing Statistical Interactions in Black Box Models M. Britton FAtt 9 20 0 01 Apr 2019
Boolean Decision Rules via Column Generation S. Dash Oktay Gunluk Dennis L. Wei 16 174 0 24 May 2018