Uses of Interface
gov.sandia.cognition.factory.Factory

Packages that use Factory

Package	Description
gov.sandia.cognition.factory	Provides interfaces and implementations of general factory objects.
gov.sandia.cognition.learning.algorithm.clustering	Provides clustering algorithms.
gov.sandia.cognition.learning.algorithm.ensemble	Provides ensemble methods.
gov.sandia.cognition.learning.performance.categorization	Provides performance measures for categorizers.
gov.sandia.cognition.statistics	Provides the inheritance hierarchy for general statistical methods and distributions.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.
gov.sandia.cognition.statistics.distribution	Provides statistical distributions.

Uses of Factory in gov.sandia.cognition.factory

Classes in gov.sandia.cognition.factory that implement Factory

Modifier and Type	Class and Description
class	ConstructorBasedFactory<CreatedType> The ConstructorBasedFactory class implements a Factory that takes a constructor and parameters to that constructor used to create new objects.
class	DefaultFactory<CreatedType> The DefaultFactory class is a default implementation of the Factory interface that takes a class as its parameter and uses the default constructor of the class, called through newInstance(), to create new objects of that class.
class	PrototypeFactory<CreatedType extends CloneableSerializable> The PrototypeFactory class implements a Factory that uses a prototype object to create new objects from by cloning it.

Uses of Factory in gov.sandia.cognition.learning.algorithm.clustering

Classes in gov.sandia.cognition.learning.algorithm.clustering that implement Factory

Modifier and Type	Class and Description
class	KMeansFactory Creates a parallelized version of the k-means clustering algorithm for the typical use: clustering vector data with a Euclidean distance metric.

Uses of Factory in gov.sandia.cognition.learning.algorithm.ensemble

Fields in gov.sandia.cognition.learning.algorithm.ensemble declared as Factory

Modifier and Type	Field and Description
protected Factory<? extends DataDistribution<CategoryType>>	IVotingCategorizerLearner.counterFactory Factory for counting votes.

Methods in gov.sandia.cognition.learning.algorithm.ensemble that return Factory

Modifier and Type	Method and Description
Factory<? extends DataDistribution<CategoryType>>	IVotingCategorizerLearner.getCounterFactory() Gets the factory used for creating the object for counting the votes of the learned ensemble members.

Methods in gov.sandia.cognition.learning.algorithm.ensemble with parameters of type Factory

Modifier and Type	Method and Description
void	IVotingCategorizerLearner.setCounterFactory(Factory<? extends DataDistribution<CategoryType>> counterFactory) Sets the factory used for creating the object for counting the votes of the learned ensemble members.

Constructors in gov.sandia.cognition.learning.algorithm.ensemble with parameters of type Factory

Constructor and Description
CategoryBalancedIVotingLearner(BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner, int maxIterations, double percentToSample, double proportionIncorrectInSample, boolean voteOutOfBagOnly, Factory<? extends DataDistribution<CategoryType>> counterFactory, java.util.Random random) Creates a new CategoryBalancedIVotingLearner.
IVotingCategorizerLearner(BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>> learner, int maxIterations, double percentToSample, double proportionIncorrectInSample, boolean voteOutOfBagOnly, Factory<? extends DataDistribution<CategoryType>> counterFactory, java.util.Random random) Creates a new IVotingCategorizerLearner.

Uses of Factory in gov.sandia.cognition.learning.performance.categorization

Classes in gov.sandia.cognition.learning.performance.categorization that implement Factory

Modifier and Type	Class and Description
static class	DefaultConfusionMatrix.Factory<CategoryType> A factory for default confusion matrices.

Fields in gov.sandia.cognition.learning.performance.categorization declared as Factory

Modifier and Type	Field and Description
protected Factory<? extends ConfusionMatrix<CategoryType>>	ConfusionMatrixPerformanceEvaluator.factory The factory used to create the confusion matrix of the evaluator.

Methods in gov.sandia.cognition.learning.performance.categorization that return Factory

Modifier and Type	Method and Description
Factory<? extends ConfusionMatrix<CategoryType>>	ConfusionMatrixPerformanceEvaluator.getFactory() Gets the factory for the confusion matrix the evaluator creates.

Methods in gov.sandia.cognition.learning.performance.categorization with parameters of type Factory

Modifier and Type	Method and Description
void	ConfusionMatrixPerformanceEvaluator.setFactory(Factory<? extends ConfusionMatrix<CategoryType>> factory) Sets the factory for the confusion matrix the evaluator creates.

Constructors in gov.sandia.cognition.learning.performance.categorization with parameters of type Factory

Constructor and Description
ConfusionMatrixPerformanceEvaluator(Factory<? extends ConfusionMatrix<CategoryType>> factory) Creates a new ConfusionMatrixPerformanceEvaluator using the given factory.

Uses of Factory in gov.sandia.cognition.statistics

Subinterfaces of Factory in gov.sandia.cognition.statistics

Modifier and Type	Interface and Description
interface	SufficientStatistic<DataType,DistributionType> Sufficient statistics are the data which are sufficient to store all information to create an underlying parameter, such as a Distribution.

Classes in gov.sandia.cognition.statistics that implement Factory

Modifier and Type	Class and Description
class	AbstractSufficientStatistic<DataType,DistributionType> Partial implementation of SufficientStatistic

Uses of Factory in gov.sandia.cognition.statistics.bayesian

Classes in gov.sandia.cognition.statistics.bayesian that implement Factory

Modifier and Type	Class and Description
class	BayesianLinearRegression.IncrementalEstimator.SufficientStatistic SufficientStatistic for incremental Bayesian linear regression
class	BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic SufficientStatistic for incremental Bayesian linear regression

Uses of Factory in gov.sandia.cognition.statistics.distribution

Classes in gov.sandia.cognition.statistics.distribution that implement Factory

Modifier and Type	Class and Description
static class	DefaultDataDistribution.DefaultFactory<DataType> A factory for DefaultDataDistribution objects using some given initial capacity for them.
static class	MultivariateGaussian.SufficientStatistic Implements the sufficient statistics of the MultivariateGaussian.
static class	MultivariateGaussian.SufficientStatisticCovarianceInverse Implements the sufficient statistics of the MultivariateGaussian while estimating the inverse of the covariance matrix.
static class	UnivariateGaussian.SufficientStatistic Captures the sufficient statistics of a UnivariateGaussian, which are the values to estimate the mean and variance.