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averagedOneDependenceEstimators from group nz.ac.waikato.cms.weka (version 1.2.1)

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24.

Group: nz.ac.waikato.cms.weka Artifact: averagedOneDependenceEstimators
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Artifact averagedOneDependenceEstimators
Group nz.ac.waikato.cms.weka
Version 1.2.1
Last update 20. July 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/averagedOneDependenceEstimators
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
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