Uncertainty in Artificial Intelligence
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Staged Mixture Modelling and Boosting
Christopher Meek, Bo Thiesson, David Heckerman
Abstract:
In this paper, we introduce and evaluate a data-driven staged mixture modeling technique for building density, regression, and classification models. Our basic approach is to sequentially add components to a finite mixture model using the structural expectation maximization (SEM) algorithm. We show that our technique is qualitatively similar to boosting. This correspondence is a natural byproduct of the fact that we use the SEM algorithm to sequentially fit the mixture model. Finally, in our experimental evaluation, we demonstrate the effectiveness of our approach on a variety of prediction and density estimation tasks using real-world data.
Keywords:
Pages: 335-343
PS Link:
PDF Link: /papers/02/p335-meek.pdf
BibTex:
@INPROCEEDINGS{Meek02,
AUTHOR = "Christopher Meek and Bo Thiesson and David Heckerman",
TITLE = "Staged Mixture Modelling and Boosting",
BOOKTITLE = "Proceedings of the Eighteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-02)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2002",
PAGES = "335--343"
}


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