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

Packages that use AbstractBatchAndIncrementalLearner
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   
gov.sandia.cognition.learning.algorithm.ensemble Provides ensmble 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
 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
 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
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
 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
 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
 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
 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
 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
 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
 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
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
static class SimpleStatisticalSpellingCorrector.Learner
          A learner for the SimpleStatisticalSpellingCorrector.