Particle Gibbs for Bayesian additive regression trees
Additive regression trees are flexible non-parametric models and popular off-the-shelf tools for real-world non-linear regression. In application domains, such as bioinformatics, where there is also demand for probabilistic predictions with measures of uncertainty, the Bayesian additive regression t...
| Main Authors: | , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
Proceedings of Machine Learning Research
2015
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