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Strong Optimal Classification Trees

Strong Optimal Classification Trees

29 March 2021
S. Aghaei
Andrés Gómez
P. Vayanos
ArXivPDFHTML

Papers citing "Strong Optimal Classification Trees"

11 / 11 papers shown
Title
Learning Optimal Classification Trees Robust to Distribution Shifts
Learning Optimal Classification Trees Robust to Distribution Shifts
Nathan Justin
S. Aghaei
Andrés Gómez
P. Vayanos
OOD
42
0
0
26 Oct 2023
Rolling Lookahead Learning for Optimal Classification Trees
Rolling Lookahead Learning for Optimal Classification Trees
Z. B. Organ
Enis Kayış
Taghi Khaniyev
21
0
0
21 Apr 2023
Supervised Feature Compression based on Counterfactual Analysis
Supervised Feature Compression based on Counterfactual Analysis
V. Piccialli
Dolores Romero Morales
Cecilia Salvatore
CML
32
2
0
17 Nov 2022
Margin Optimal Classification Trees
Margin Optimal Classification Trees
Federico DÓnofrio
G. Grani
Marta Monaci
L. Palagi
28
10
0
19 Oct 2022
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal
  Treatment Regimes and Optimal Policy Design
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design
Ali Behrouz
Mathias Lécuyer
Cynthia Rudin
Margo Seltzer
OffRL
23
2
0
13 Oct 2022
Exploring the Whole Rashomon Set of Sparse Decision Trees
Exploring the Whole Rashomon Set of Sparse Decision Trees
Rui Xin
Chudi Zhong
Zhi Chen
Takuya Takagi
Margo Seltzer
Cynthia Rudin
43
54
0
16 Sep 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of
  tree-based methods
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
Abhineet Agarwal
Yan Shuo Tan
Omer Ronen
Chandan Singh
Bin-Xia Yu
65
27
0
02 Feb 2022
A cautionary tale on fitting decision trees to data from additive
  models: generalization lower bounds
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan
Abhineet Agarwal
Bin Yu
27
10
0
18 Oct 2021
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
33
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
341
4,230
0
23 Aug 2019
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
2,091
0
24 Oct 2016
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