decision trees
Decision trees are a type of predictive model that use a tree-like graph of decisions and their possible consequences. In AI, they are used for classification and regression tasks by breaking down data into simplistic, interpretable decision rules.
- Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
- Empowering Decision Trees via Shape Function Branching
- Fréchet Geodesic Boosting
- Improving Decision Trees through the Lens of Parameterized Local Search
- SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
- TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning