Bayesian Treed Generalized Linear Models

By Hugh A. Chipman, Edward I. George, Robert E. McCulloch. 2003

22 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Satoshi Hara
2. Jialei Wang
3. Kohei Hayashi
4. Markus Svensén
5. Charles M. Bishop
6. Neil D. Lawrence
7. Ryohei Fujimaki
8. Yosuke Motohashi

Citations in the corpus

• Making Tree Ensembles Interpretable (2016, methodology): “, 1994) and Bayesian treed linear models (Chipman et al., 2003) extended the decision tree by replacing single-feature partitioning with linear hyperplane partitioning and the region-wise constant predictor with the linear model.”
• Bayesian Hierarchical Mixtures of Experts (2002, methodology): “For larger trees, we could consider using greedy search algorithms (Ueda and Ghahramani 2002) or Monte-Carlo methods (Chipman, George, and McCulloch 2002).”
• Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models (2015, background): “Oblique decision trees [ 33] extend region specifiers from single-feature thresholding to linear hyperplanes, and Bayesian treed linear models (BTLMs) [8] employ linear hyperplanes for region-specific predictors.”