Publications [#312733] of Merlise Clyde
Papers Published
- Clyde, M; Lee, HK. "Bagging and the Bayesian Bootstrap." Artificial Intelligence and StatisticsArtificial Intelligence and Statistics 2001 8 (2001): 169-174. [ps]
(last updated on 2026/02/08)Abstract:
Bagging is a method of obtaining more ro- bust predictions when the model class under consideration is unstable with respect to the data, i.e., small changes in the data can cause the predicted values to change significantly. In this paper, we introduce a Bayesian ver- sion of bagging based on the Bayesian boot- strap. The Bayesian bootstrap resolves a the- oretical problem with ordinary bagging and often results in more efficient estimators. We show how model averaging can be combined within the Bayesian bootstrap and illustrate the procedure with several examples.