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## Package weka.classifiers.bayes

Class Summary
AODE | 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.
AODEsr | AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value. For more information, see: Fei Zheng, Geoffrey I.
BayesianLogisticRegression | Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors. For more information, see Alexander Genkin, David D.
BayesNet | Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.
ComplementNaiveBayes | Class for building and using a Complement class Naive Bayes classifier. For more information see, Jason D.
DMNBtext | Class for building and using a Discriminative Multinomial Naive Bayes classifier.
HNB | Contructs Hidden Naive Bayes classification model with high classification accuracy and AUC. For more information refer to: H.
NaiveBayes | Class for a Naive Bayes classifier using estimator classes.
NaiveBayesMultinomial | Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesMultinomialUpdateable | Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesSimple | Class for building and using a simple Naive Bayes classifier.Numeric attributes are modelled by a normal distribution. For more information, see Richard Duda, Peter Hart (1973).
NaiveBayesUpdateable | Class for a Naive Bayes classifier using estimator classes.
WAODE | WAODE contructs the model called Weightily Averaged One-Dependence Estimators. For more information, see L.

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