Basilio Sierra, Nicolás Serrano, Pedro Larrañaga, Eliseo J. Plasencia, Iñaki Inza, Juan José Jiménez, Pedro Revuelta, María Luisa Mora  Home/Search
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Abstract: Combining the predictions of a set of classifiers has shown to be an effective way to create composite classifiers that are more accurate than any of the component classifiers. There are many methods for combining the predictions given by component classifiers. We introduce a new method that combine a number of component classifiers using a Bayesian network as a classifier system given the component classifiers predictions. Component classifiers are standard machine learning classification ... (Update)
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BibTeX entry: (Update)
B. Sierra, N. Serrano, P. Larra naga, E.J. Plasencia, I. Inza, J.J. Jim enez, P. Revuelta, and M.L. Mora, `Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data', Artificial Intelligence in Medicine, 22, 233--248, (2001). 2 http://citeseer.ist.psu.edu/article/sierra00using.html More
@article{ sierra01using,
author = "Basilio Sierra and Nicolas Serrano and Pedro Larranaga and Eliseo J. Plasencia and Inaki Inza and Juan Jose Jimenez and Pedro Revuelta and Maria Luisa Mora",
title = "Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data",
journal = "Artificial Intelligence in Medicine",
volume = "22",
number = "3",
pages = "233-248",
year = "2001",
url = "citeseer.ist.psu.edu/article/sierra00using.html" }
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