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Strong Optimal Classification Trees
v1v2v3 (latest)

Strong Optimal Classification Trees

Operational Research (OR), 2021
29 March 2021
S. Aghaei
Andrés Gómez
P. Vayanos
ArXiv (abs)PDFHTML

Papers citing "Strong Optimal Classification Trees"

21 / 21 papers shown
A Unified Optimization Framework for Multiclass Classification with Structured Hyperplane Arrangements
A Unified Optimization Framework for Multiclass Classification with Structured Hyperplane Arrangements
Víctor Blanco
Harshit Kothari
James Luedtke
84
0
0
06 Oct 2025
Proper decision trees: An axiomatic framework for solving optimal decision tree problems with arbitrary splitting rules
Proper decision trees: An axiomatic framework for solving optimal decision tree problems with arbitrary splitting rules
Xi He
Max A. Little
217
2
0
03 Mar 2025
Learning Optimal Signal Temporal Logic Decision Trees for
  Classification: A Max-Flow MILP Formulation
Learning Optimal Signal Temporal Logic Decision Trees for Classification: A Max-Flow MILP Formulation
Kaier Liang
Gustavo A. Cardona
Disha Kamale
C. Vasile
200
1
0
30 Jul 2024
Optimization Over Trained Neural Networks: Taking a Relaxing Walk
Optimization Over Trained Neural Networks: Taking a Relaxing Walk
Jiatai Tong
Junyang Cai
Thiago Serra
377
14
0
07 Jan 2024
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
493
2
0
26 Oct 2023
ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription
ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription
Patrick Vossler
S. Aghaei
Nathan Justin
Nathanael Jo
Andrés Gómez
P. Vayanos
213
2
0
28 Jul 2023
Loss-Optimal Classification Trees: A Generalized Framework and the
  Logistic Case
Loss-Optimal Classification Trees: A Generalized Framework and the Logistic CaseTOP - An Official Journal of the Spanish Society of Statistics and Operations Research (TOP), 2023
Tommaso Aldinucci
Matteo Lapucci
228
0
0
01 Jun 2023
Rolling Lookahead Learning for Optimal Classification Trees
Rolling Lookahead Learning for Optimal Classification Trees
Z. B. Organ
Enis Kayış
Taghi Khaniyev
154
0
0
21 Apr 2023
Scalable Optimal Multiway-Split Decision Trees with Constraints
Scalable Optimal Multiway-Split Decision Trees with ConstraintsAAAI Conference on Artificial Intelligence (AAAI), 2023
Shivaram Subramanian
Wei-Ju Sun
120
4
0
14 Feb 2023
Supervised Feature Compression based on Counterfactual Analysis
Supervised Feature Compression based on Counterfactual AnalysisEuropean Journal of Operational Research (EJOR), 2022
V. Piccialli
Dolores Romero Morales
Cecilia Salvatore
CML
257
2
0
17 Nov 2022
Margin Optimal Classification Trees
Margin Optimal Classification TreesComputers & Operations Research (COR), 2022
Federico DÓnofrio
G. Grani
Marta Monaci
L. Palagi
419
15
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
224
2
0
13 Oct 2022
Exploring the Whole Rashomon Set of Sparse Decision Trees
Exploring the Whole Rashomon Set of Sparse Decision TreesNeural Information Processing Systems (NeurIPS), 2022
Rui Xin
Chudi Zhong
Zhi Chen
Takuya Takagi
Margo Seltzer
Cynthia Rudin
305
77
0
16 Sep 2022
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees
  with Continuous Features
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous FeaturesInternational Conference on Machine Learning (ICML), 2022
Rahul Mazumder
X. Meng
Haoyue Wang
124
19
0
23 Jun 2022
Mixed integer linear optimization formulations for learning optimal
  binary classification trees
Mixed integer linear optimization formulations for learning optimal binary classification trees
B. Alston
Hamidreza Validi
Illya V. Hicks
175
3
0
10 Jun 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of
  tree-based methods
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methodsInternational Conference on Machine Learning (ICML), 2022
Abhineet Agarwal
Yan Shuo Tan
Omer Ronen
Chandan Singh
Bin Yu
189
32
0
02 Feb 2022
Learning Optimal Fair Classification Trees: Trade-offs Between
  Interpretability, Fairness, and Accuracy
Learning Optimal Fair Classification Trees: Trade-offs Between Interpretability, Fairness, and AccuracyAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2022
Nathanael Jo
S. Aghaei
A. Gómez
P. Vayanos
FaML
476
25
0
24 Jan 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
202
12
0
18 Oct 2021
Learning Optimal Prescriptive Trees from Observational Data
Learning Optimal Prescriptive Trees from Observational Data
Nathanael Jo
S. Aghaei
Andrés Gómez
P. Vayanos
218
22
0
31 Aug 2021
Rule Generation for Classification: Scalability, Interpretability, and Fairness
Rule Generation for Classification: Scalability, Interpretability, and FairnessComputers & Operations Research (Comput. Oper. Res.), 2021
Tabea E. Rober
Adia C. Lumadjeng
M. Akyuz
cS. .Ilker Birbil
518
4
0
21 Apr 2021
Conjecturing-Based Discovery of Patterns in Data
Conjecturing-Based Discovery of Patterns in DataINFORMS Journal on Data Science (JIDS), 2020
J. Brooks
David J. Edwards
Craig E. Larson
N. Van Cleemput
182
2
0
23 Nov 2020
1