averagedOneDependenceEstimators: Family of methods for learning ensembles of naive Bayes-like classifiers (with relaxed independence assumption) - includes AODE, WAODE and AODEsr

NOTE: This package has been superseded by the AnDE (Averaged N Dependence Estimators) package - all users are encouraged to use this instead. 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.

All available versions:
Latest
1.2.1
1.2.0
1.0.1
1.0.0