Robust inference of trees
This paper is concerned with the reliable inference of optimal tree-approximations to the dependency structure of an unknown distribution generating data. The traditional approach to the problem measures the dependency strength between random variables by the index called mutual information. In this paper reliability is achieved by Walley’s imprecise Dirichlet model, which generalizes Bayesian learning with Dirichlet priors. Adopting the imprecise Dirichlet model results in posterior...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Mathematics and Artificial Intelligence|
|Hutter and Zaffalon Robust Inference of Trees 2005.pdf||269.43 kB||Adobe PDF|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.