# All Classes and Interfaces

Classes
Class
Description
BinaryNaiveBayesModelReader
A `NaiveBayesModelReader` that reads models from a binary format.
BinaryNaiveBayesModelWriter
A `NaiveBayesModelWriter` that writes models in a binary format.
LogProbabilities<T>
Class implementing the probability distribution over labels returned by a classifier as a log of probabilities.
LogProbability<T>
A class implementing the logarithmic `Probability` for a label.
NaiveBayesEvalParameters
Specialized `parameters` for the evaluation of a naive bayes classifier
NaiveBayesModel
A `MaxentModel` implementation of the multinomial Naive Bayes classifier model.
NaiveBayesModelReader
The base class for readers of `models`.
NaiveBayesModelWriter
The base class for `NaiveBayesModel` writers.
NaiveBayesTrainer
Trains `models` using the combination of EM algorithm and Naive Bayes classifier which is described in:
PlainTextNaiveBayesModelReader
A `NaiveBayesModelReader` that reads models from a plain text format.
PlainTextNaiveBayesModelWriter
A `NaiveBayesModelWriter` that writes models in a 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.