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Interpretable and Fair Boolean Rule Sets via Column Generation

Interpretable and Fair Boolean Rule Sets via Column Generation

16 November 2021
Connor Lawless
S. Dash
Oktay Gunluk
Dennis L. Wei
    FaML
ArXivPDFHTML

Papers citing "Interpretable and Fair Boolean Rule Sets via Column Generation"

6 / 6 papers shown
Title
Understanding Fixed Predictions via Confined Regions
Understanding Fixed Predictions via Confined Regions
Connor Lawless
Tsui-Wei Weng
Berk Ustun
Madeleine Udell
48
0
0
22 Feb 2025
Explaining with Greater Support: Weighted Column Sampling Optimization
  for q-Consistent Summary-Explanations
Explaining with Greater Support: Weighted Column Sampling Optimization for q-Consistent Summary-Explanations
Chen Peng
Zhengqi Dai
Guangping Xia
Yajie Niu
Yihui Lei
23
0
0
09 Feb 2023
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Tabea E. Rober
Adia C. Lumadjeng
M. Akyuz
cS. .Ilker Birbil
19
2
0
21 Apr 2021
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
Learning Certifiably Optimal Rule Lists for Categorical Data
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
48
195
0
06 Apr 2017
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,082
0
24 Oct 2016
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