Namespace NOpenNLP.Tools.Ml.Naivebayes
Classes
- 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. This is necessary because floating point precision in Java does not allow for high-accuracy representation of very low probabilities such as would occur in a text categorizer.
- 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. It provides the persist method which takes care of the structure of a stored document, and requires an extending class to define precisely how the data should be stored.
- 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
- 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.