Uses of Class
gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner

Packages that use AbstractBatchAndIncrementalLearner

Package	Description
gov.sandia.cognition.learning.algorithm	Provides general interfaces for learning algorithms.
gov.sandia.cognition.learning.algorithm.bayes	Provides algorithms for computing Bayesian categorizers.
gov.sandia.cognition.learning.algorithm.confidence	Provides confidence-weighted categorization algorithms.
gov.sandia.cognition.learning.algorithm.ensemble	Provides ensemble methods.
gov.sandia.cognition.learning.algorithm.perceptron	Provides the Perceptron algorithm and some of its variations.
gov.sandia.cognition.learning.algorithm.perceptron.kernel
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.bayesian.conjugate	Provides Bayesian estimation routines based on conjugate prior distribution of parameters of specific conditional distributions.
gov.sandia.cognition.statistics.distribution	Provides statistical distributions.
gov.sandia.cognition.text.spelling	Provides classes for spelling.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm

Modifier and Type	Class and Description
class	AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> An abstract implementation of the batch and incremental learning for an incremental supervised learner.

Methods in gov.sandia.cognition.learning.algorithm that return AbstractBatchAndIncrementalLearner

Modifier and Type	Method and Description
AbstractBatchAndIncrementalLearner<DataType,ResultType>	AbstractBatchAndIncrementalLearner.clone()

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.bayes

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.bayes

Modifier and Type	Class and Description
static class	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.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.confidence

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.confidence

Modifier and Type	Class and Description
class	AdaptiveRegularizationOfWeights An implementation of the Adaptive Regularization of Weights (AROW) algorithm for online learning of a linear binary categorizer.
class	ConfidenceWeightedDiagonalDeviation An implementation of the Standard Deviation (Stdev) algorithm for learning a confidence-weighted categorizer.
class	ConfidenceWeightedDiagonalDeviationProject An implementation of the Standard Deviation (Stdev) algorithm for learning a confidence-weighted categorizer.
class	ConfidenceWeightedDiagonalVariance An implementation of the Variance algorithm for learning a confidence-weighted linear categorizer.
class	ConfidenceWeightedDiagonalVarianceProject An implementation of the Variance algorithm for learning a confidence-weighted linear categorizer.

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

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.ensemble

Modifier and Type	Class and Description
class	OnlineBaggingCategorizerLearner<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>> An implementation of an online version of the Bagging algorithm for learning an ensemble of categorizers.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.perceptron

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.perceptron

Modifier and Type	Class and Description
class	AbstractKernelizableBinaryCategorizerOnlineLearner An abstract implementation of the KernelizableBinaryCategorizerOnlineLearner interface.
class	AbstractLinearCombinationOnlineLearner An abstract class for online learning of linear binary categorizers that take the form of a weighted sum of inputs.
class	AbstractOnlineLinearBinaryCategorizerLearner An abstract class for online (incremental) learning algorithms that produce an LinearBinaryCategorizer.
class	AggressiveRelaxedOnlineMaximumMarginAlgorithm An implementation of the Aggressive Relaxed Online Maximum Margin Algorithm (AROMMA).
class	Ballseptron An implementation of the Ballseptron algorithm.
class	OnlineBinaryMarginInfusedRelaxedAlgorithm An implementation of the binary MIRA algorithm.
class	OnlineMultiPerceptron<CategoryType> An online, multiple category version of the Perceptron algorithm.
static class	OnlineMultiPerceptron.ProportionalUpdate<CategoryType> Variant of a multi-category Perceptron that performs a proportional weight update on all categories that are scored higher than the true category such that the weights sum to 1.0 and are proportional how much larger the score was for each incorrect category than the true category.
static class	OnlineMultiPerceptron.UniformUpdate<CategoryType> Variant of a multi-category Perceptron that performs a uniform weight update on all categories that are scored higher than the true category such that the weights are equal and sum to -1.
class	OnlinePassiveAggressivePerceptron An implementation of the Passive-Aggressive algorithm for learning a linear binary categorizer.
static class	OnlinePassiveAggressivePerceptron.AbstractSoftMargin An abstract class for soft-margin versions of the Passive-Aggressive algorithm.
static class	OnlinePassiveAggressivePerceptron.LinearSoftMargin An implementation of the linear soft-margin variant of the Passive- Aggressive algorithm (PA-I).
static class	OnlinePassiveAggressivePerceptron.QuadraticSoftMargin An implementation of the quadratic soft-margin variant of the Passive- Aggressive algorithm (PA-II).
class	OnlinePerceptron An online version of the classic Perceptron algorithm.
class	OnlineRampPassiveAggressivePerceptron An implementation of the Ramp Loss Passive Aggressive Perceptron (PA^R) from the referenced paper.
class	OnlineShiftingPerceptron An implementation of the Shifting Perceptron algorithm.
class	OnlineVotedPerceptron An online version of the Voted-Perceptron algorithm.
class	RelaxedOnlineMaximumMarginAlgorithm An implementation of the Relaxed Online Maximum Margin Algorithm (ROMMA).
class	Winnow An implementation of the Winnow incremental learning algorithm.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.perceptron.kernel

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.learning.algorithm.perceptron.kernel

Modifier and Type	Class and Description
class	AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> An abstract implementation of the BudgetedKernelBinaryCategorizerLearner for online learners.
class	AbstractOnlineKernelBinaryCategorizerLearner<InputType> An abstract class for an online kernel binary categorizer learner.
class	Forgetron<InputType> An implementation of the "self-tuned" Forgetron algorithm, which is an online budgeted kernel binary categorizer learner.
static class	Forgetron.Basic<InputType> An implementation of the "basic" Forgetron algorithm, which is an online budgeted kernel binary categorizer learner.
static class	Forgetron.Greedy<InputType> An implementation of the "greedy" Forgetron algorithm, which is an online budgeted kernel binary categorizer learner.
class	KernelBinaryCategorizerOnlineLearnerAdapter<InputType> A wrapper class for a KernelizableBinaryCategorizerOnlineLearner that allows it to be used as a batch or incremental learner over the input type directly, rather than using utility methods.
class	OnlineKernelPerceptron<InputType> An implementation of the online version of the Perceptron algorithm.
class	OnlineKernelRandomizedBudgetPerceptron<InputType> An implementation of a fixed-memory kernel Perceptron algorithm.
class	Projectron<InputType> An implementation of the Projectron algorithm, which is an online kernel binary categorizer learner that has a budget parameter tuned by the eta parameter.
static class	Projectron.LinearSoftMargin<InputType> An implementation of the Projectron++ algorithm, which is an online kernel binary categorizer learner that has a budget parameter tuned by the eta parameter.
class	RemoveOldestKernelPerceptron<InputType> A budget kernel Perceptron that always removes the oldest item.
class	Stoptron<InputType> An online, budgeted, kernel version of the Perceptron algorithm that stops learning once it has reached its budget.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics

Modifier and Type	Class and Description
class	AbstractIncrementalEstimator<DataType,DistributionType extends Distribution<? extends DataType>,SufficientStatisticsType extends SufficientStatistic<DataType,DistributionType>> Partial implementation of IncrementalEstimator.

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

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics.bayesian

Modifier and Type	Class and Description
class	AbstractKalmanFilter Contains fields useful to both Kalman filters and extended Kalman filters.
class	AbstractParticleFilter<ObservationType,ParameterType> Partial abstract implementation of ParticleFilter.
class	ExtendedKalmanFilter Implements the Extended Kalman Filter (EKF), which is an extension of the Kalman filter that allows nonlinear motion and observation models.
class	KalmanFilter A Kalman filter estimates the state of a dynamical system corrupted with white Gaussian noise with observations that are corrupted with white Gaussian noise.
class	SamplingImportanceResamplingParticleFilter<ObservationType,ParameterType> An implementation of the standard Sampling Importance Resampling particle filter.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics.bayesian.conjugate

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics.bayesian.conjugate

Modifier and Type	Class and Description
class	AbstractConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> Partial implementation of ConjugatePriorBayesianEstimator that contains a initial belief (prior) distribution function.
class	BernoulliBayesianEstimator A Bayesian estimator for the parameter of a BernoulliDistribution using the conjugate prior BetaDistribution.
class	BinomialBayesianEstimator A Bayesian estimator for the parameter of a Bernoulli parameter, p, of a BinomialDistribution using the conjugate prior BetaDistribution.
class	ExponentialBayesianEstimator Conjugate prior Bayesian estimator of the "rate" parameter of an Exponential distribution using the conjugate prior Gamma distribution.
class	GammaInverseScaleBayesianEstimator A Bayesian estimator for the scale parameter of a Gamma distribution using the conjugate prior Gamma distribution for the inverse-scale (rate) of the Gamma.
class	MultinomialBayesianEstimator A Bayesian estimator for the parameters of a MultinomialDistribution using its conjugate prior distribution, the DirichletDistribution.
class	MultivariateGaussianMeanBayesianEstimator Bayesian estimator for the mean of a MultivariateGaussian using its conjugate prior, which is also a MultivariateGaussian.
class	MultivariateGaussianMeanCovarianceBayesianEstimator Performs robust estimation of both the mean and covariance of a MultivariateGaussian conditional distribution using the conjugate prior Normal-Inverse-Wishart distribution.
class	PoissonBayesianEstimator A Bayesian estimator for the parameter of a PoissonDistribution using the conjugate prior GammaDistribution.
class	UniformDistributionBayesianEstimator A Bayesian estimator for a conditional Uniform(0,theta) distribution using its conjugate prior Pareto distribution.
class	UnivariateGaussianMeanBayesianEstimator Bayesian estimator for the mean of a UnivariateGaussian using its conjugate prior, which is also a UnivariateGaussian.
class	UnivariateGaussianMeanVarianceBayesianEstimator Computes the mean and variance of a univariate Gaussian using the conjugate prior NormalInverseGammaDistribution

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

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.statistics.distribution

Modifier and Type	Class and Description
static class	DefaultDataDistribution.Estimator<KeyType> Estimator for a DefaultDataDistribution
static class	DefaultDataDistribution.WeightedEstimator<KeyType> A weighted estimator for a DefaultDataDistribution
static class	MultivariateGaussian.IncrementalEstimator The estimator that creates a MultivariateGaussian from a stream of values.
static class	MultivariateGaussian.IncrementalEstimatorCovarianceInverse The estimator that creates a MultivariateGaussian from a stream of values by estimating the mean and covariance inverse (as opposed to the covariance directly), without ever performing a matrix inversion.
static class	ScalarDataDistribution.Estimator Estimator for a ScalarDataDistribution
static class	UnivariateGaussian.IncrementalEstimator Implements an incremental estimator for the sufficient statistics for a UnivariateGaussian.

Uses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.text.spelling

Subclasses of AbstractBatchAndIncrementalLearner in gov.sandia.cognition.text.spelling

Modifier and Type	Class and Description
static class	SimpleStatisticalSpellingCorrector.Learner A learner for the SimpleStatisticalSpellingCorrector.