English
español
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10261/3019
Share/Impact:
Statistics |
![]() ![]() |
|
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | ||
|
Title: | TAN Classifiers Based on Decomposable Distributions |
Authors: | Cerquides, Jesús ; López de Mántaras, Ramón |
Keywords: | Artificial Intelligence Bayesian networks classifiers Naive Bayes Tree augmented naive Bayes Decomposable distributions Bayesian model averaging |
Issue Date: | 2005 |
Publisher: | Springer |
Citation: | Machine Learning, 2005, 59 (3): 323-354 |
Abstract: | In this paper we present several Bayesian algorithms for learning Tree Augmented Naive Bayes (TAN) models. We extend the results in Meila & Jaakkola (2000a) to TANs by proving that accepting a prior decomposable distribution over TAN's, we can compute the exact Bayesian model averaging over TAN structures and parameters in polynomial time. Furthermore, we prove that the k-maximum a posteriori (MAP) TAN structures can also be computed in polynomial time. We use these results to correct minor errors in Meila & Jaakkola (2000a) and to construct several TAN based classifiers provide consistently better predictions over Irvine datasets and artificially generated data than TAN based classifiers proposed in the literature. |
Description: | The original publication is available at www.springerlink.com |
URI: | http://hdl.handle.net/10261/3019 |
ISSN: | 0885-6125 |
Appears in Collections: | (IIIA) Artículos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
TR-2004-01.pdf | 416,09 kB | Adobe PDF | ![]() View/Open |
Show full item record
Review this work
Review this work
WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.