Research map / Learning theory and algorithms / Combinatorial and search optimization
Learning Optimal Classification Trees Using a Binary Linear Program Formulation
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| binary-search encoding of thresholds with aggregated big-M constraints (BinOCT) vs OCT | MIP decision tree learning · UCI datasets depth 2-3 | test accuracy: Monks-1 depth 2: 67.7 -> 80.0 | Helped |
| BinOCT vs CART | decision tree learning · UCI datasets depth 4 | test accuracy: Statlog-sat 79.9 -> 65.9 | Hurt |
| warm start from CART solution (ablation) | BinOCT · Statlog-sat depth 4 | test accuracy: 65.9 -> 79.9 | Helped |
| warm start from CART solution (ablation) | BinOCT · UCI datasets depth 2-3 | training accuracy | No clear effect |
| BinOCT vs DTIPs | MIP decision tree learning · Balance-scale, Bank marketing, PI-diabetes | training accuracy: PI-diabetes depth 2: 77.7 -> 79.3 | Helped |
| BinOCT vs OCT | MIP decision tree learning · Wine | test accuracy: 94.2 -> 88.0 (depth 3) | Hurt |
Closest papers by meaning
- Optimal Classification Trees for Continuous Feature Data Using Dynamic Programming with Branch-and-Bound (AAAI 2025 · similarity 0.90)
- Learning Small Decision Trees for Data of Low Rank-Width (AAAI 2024 · similarity 0.86)
- Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach (ICML 2024 · similarity 0.85)
- Improving Decision Trees through the Lens of Parameterized Local Search (NeurIPS 2025 · similarity 0.85)
- Optimal Decision Tree Pruning Revisited: Algorithms and Complexity (ICML 2025 · similarity 0.85)
- Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO* (ICML 2025 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.