D3M-Research-Group / odtlearn
A package for tree-based statistical estimation and inference using optimal decision trees.
☆40Updated 6 months ago
Alternatives and similar repositories for odtlearn:
Users that are interested in odtlearn are comparing it to the libraries listed below
- OCEAN: Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)☆20Updated 11 months ago
- ☆31Updated 4 years ago
- ☆31Updated 4 months ago
- Code for "Explainable Data-Driven Optimization" (ICML 2023)☆15Updated last year
- Code the AAAI 2019 paper "Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization"☆28Updated 3 years ago
- An end-to-end framework for mixed-integer optimization with data-driven learned constraints.☆118Updated last year
- The MIP Workshop 2023 Computational Competition☆41Updated 11 months ago
- Born-Again Tree Ensembles: Transforms a random forest into a single, minimal-size, tree with exactly the same prediction function in the …☆64Updated last year
- Framework for solving discrete optimization problems using a combination of Mixed-Integer Linear Programming (MIP) and Machine Learning (…☆158Updated last month
- Python Implementation of Bertsimas's "Optimal classification trees".☆33Updated 4 years ago
- Replication Code for Paper "Stochastic Optimization Forests".☆19Updated 3 years ago
- Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs☆24Updated last month
- The Machine Learning Optimizer☆101Updated last year
- ☆22Updated 3 years ago
- Learning to Compare Nodes in Branch and Bound with Graph Neural Networks (NeurIPS 2022)☆20Updated 2 years ago
- Nutmeg – a MIP and CP branch-and-check solver☆23Updated last year
- ☆42Updated 2 years ago
- ☆24Updated last month
- A standalone local search solver for general mixed integer programming☆17Updated last month
- OptiChat: Explaining Optimization Models Using LLMs☆17Updated this week
- Machine Learning for Combinatorial Optimization - NeurIPS'21 competition☆127Updated 2 years ago
- Discrete Optimization is a python library to ease the definition and re-use of discrete optimization problems and solvers.☆43Updated last month
- Combinatorial Optimization in Gurobi☆42Updated last year
- ☆24Updated last year
- Combinatorial optimization layers for machine learning pipelines☆116Updated 3 weeks ago
- Combining Reinforcement Learning with Integer Programming for Robust Scheduling☆26Updated 11 months ago
- Code release for AAAI 2020 paper "Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems"☆37Updated 6 months ago
- Hybrid Models for Learning to Branch (NeurIPS 2020)☆47Updated 3 years ago
- MIE424 Group Project: smart_predict_optimize☆13Updated 3 years ago
- The source code for the paper: 'ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problems'☆83Updated 3 years ago