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.
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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.
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BayesianLogisticRegression |
Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors.
For more information, see
Alexander Genkin, David D.
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BayesNet |
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
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ComplementNaiveBayes |
Class for building and using a Complement class Naive Bayes classifier.
For more information see,
Jason D.
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DMNBtext |
Class for building and using a Discriminative Multinomial Naive Bayes classifier.
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HNB |
Contructs Hidden Naive Bayes classification model with high classification accuracy and AUC.
For more information refer to:
H.
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NaiveBayes |
Class for a Naive Bayes classifier using estimator classes.
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NaiveBayesMultinomial |
Class for building and using a multinomial Naive Bayes classifier.
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NaiveBayesMultinomialUpdateable |
Class for building and using a multinomial Naive Bayes classifier.
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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).
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NaiveBayesUpdateable |
Class for a Naive Bayes classifier using estimator classes.
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WAODE |
WAODE contructs the model called Weightily Averaged One-Dependence Estimators.
For more information, see
L.
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