Class | Description |
---|---|
BinaryNaiveBayesModelReader | |
BinaryNaiveBayesModelWriter |
Model writer that saves models in binary format.
|
LogProbabilities<T> |
Class implementing the probability distribution over labels returned by
a classifier as a log of probabilities.
|
LogProbability<T> |
Class implementing the probability for a label.
|
NaiveBayesEvalParameters |
Parameters for the evalution of a naive bayes classifier
|
NaiveBayesModel |
Class implementing the multinomial Naive Bayes classifier model.
|
NaiveBayesModelReader |
Abstract parent class for readers of NaiveBayes.
|
NaiveBayesModelWriter |
Abstract parent class for NaiveBayes writers.
|
NaiveBayesTrainer |
Trains models using the combination of EM algorithm and Naive Bayes classifier
which is described in:
Text Classification from Labeled and Unlabeled Documents using EM
Nigam, McCallum, et al paper of 2000
|
PlainTextNaiveBayesModelReader | |
PlainTextNaiveBayesModelWriter |
Model writer that saves models in plain text format.
|
Probabilities<T> |
Class implementing the probability distribution over labels returned by a classifier.
|
Probability<T> |
Class implementing the probability for a label.
|
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