This is the Windows app named Averaged N-Dependence Estimators - AnDE whose latest release can be downloaded as AnDE1.2.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
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Averaged N-Dependence Estimators - AnDE
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DESCRIPTION
Averaged N-Dependence Estimators (A1DE and A2DE) 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 and G.I. Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. Machine Learning. 86(2):233-272.This is an application that can also be fetched from https://sourceforge.net/projects/averagedndepend/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
