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 interval...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Mathematics and Artificial Intelligence|
|01_Zaffalon_Robust_inference_of_trees_2005.pdf||269.13 kB||Adobe PDF||Request a copy|
|02_Zaffalon_Robust_inference_of_trees_2005.pdf||204.02 kB||Adobe PDF||Request a copy|
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