Package gov.sandia.cognition.learning.algorithm.bayes

Provides algorithms for computing Bayesian categorizers.

See:
          Description

Class Summary
DiscreteNaiveBayesCategorizer<InputType,CategoryType> Implementation of a Naive Bayes Classifier for Discrete Data.
DiscreteNaiveBayesCategorizer.Learner<InputType,CategoryType> Learner for a DiscreteNaiveBayesCategorizer.
VectorNaiveBayesCategorizer<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction> A naive Bayesian categorizer that takes an input vector and applies an independent scalar probability density function to each one.
VectorNaiveBayesCategorizer.BatchGaussianLearner<CategoryType> A supervised batch distributionLearner for a vector Naive Bayes categorizer that fits a Gaussian.
VectorNaiveBayesCategorizer.Learner<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction> A supervised batch distributionLearner for a vector Naive Bayes categorizer.
VectorNaiveBayesCategorizer.OnlineLearner<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction> An online (incremental) distributionLearner for the Naive Bayes categorizer that uses an incremental distribution learner for the distribution representing each dimension for each category.
 

Package gov.sandia.cognition.learning.algorithm.bayes Description

Provides algorithms for computing Bayesian categorizers.

Since:
3.0
Author:
Kevin R. Dixon