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| 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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