Katherine A. Heller, Zoubin Ghahramani  Home/Search
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Abstract: We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages over traditional distance-based agglomerative clustering algorithms. (1) It defines a probabilistic model of the data which can be used to compute the predictive distribution of a test point and the probability of it belonging to any of the existing clusters in the tree. (2) It uses a model-based criterion to... (Update)
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BibTeX entry: (Update)
@misc{ heller-bayesian,
author = "Katherine A. Heller and Zoubin Ghahramani",
title = "Bayesian Hierarchical Clustering",
url = "citeseer.ist.psu.edu/735303.html" }
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