Package com.datumbox.framework.core.machinelearning.classification

Class Summary

Class	Description
BernoulliNaiveBayes	The BernoulliNaiveBayes class implements the Bernoulli Naive Bayes model.
BernoulliNaiveBayes.ModelParameters	Base class for every ModelParameter class in the framework.
BernoulliNaiveBayes.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
BinarizedNaiveBayes	The BinarizedNaiveBayes class implements an alternative version of Multinomial Naive Bayes, in which the total number of counts of each activated feature is clipped to 1.
BinarizedNaiveBayes.ModelParameters	Base class for every ModelParameter class in the framework.
BinarizedNaiveBayes.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
MaximumEntropy	The MaximumEntropy implements the Max Ent classifier which is an alternative implementation of Multinomial Logistic Regression model.
MaximumEntropy.ModelParameters	Base class for every ModelParameter class in the framework.
MaximumEntropy.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
MultinomialNaiveBayes	The MultinomialNaiveBayes class provides an implementation of Multinomial Naive Bayes model.
MultinomialNaiveBayes.ModelParameters	Base class for every ModelParameter class in the framework.
MultinomialNaiveBayes.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
OrdinalRegression	The OrdinalRegression implements the Multinomial Ordinal Regression.
OrdinalRegression.ModelParameters	Base class for every ModelParameter class in the framework.
OrdinalRegression.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
SoftMaxRegression	The SoftMaxRegression implements the Multinomial Logistic Regression classifier.
SoftMaxRegression.ModelParameters	Base class for every ModelParameter class in the framework.
SoftMaxRegression.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.
SupportVectorMachine	The SupportVectorMachine class enables you to train SVM models.
SupportVectorMachine.ModelParameters	Base class for every ModelParameter class in the framework.
SupportVectorMachine.TrainingParameters	The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.