Machine learningMachine learning
贝叶斯决策树
贝叶斯决策树（Bayesian CART）为树结构和叶节点参数设定先验分布，然后使用马尔可夫链蒙特卡洛（MCMC）方法探索给定数据的树的后验分布。它不输出单一的最佳树，而是产生一个合理的树的分布，通过对这些树的预测进行平均来获得校准的不确定性估计以及点预测。
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来源
- Chipman, H. A., George, E. I., & McCulloch, R. E. (1998). Bayesian CART model search. Journal of the American Statistical Association, 93(443), 935–948. DOI: 10.1080/01621459.1998.10473750 ↗
- Denison, D. G. T., Mallick, B. K., & Smith, A. F. M. (1998). A Bayesian CART algorithm. Biometrika, 85(2), 363–377. link ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Decision Tree (Bayesian CART). ScholarGate. https://scholargate.app/zh/machine-learning/bayesian-decision-tree
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