gov.sandia.cognition.util
Interface CloneableSerializable

All Superinterfaces:

Cloneable, Serializable

All Known Subinterfaces:

ActivatableCogxel, AnytimeBatchLearner<DataType,ResultType>, BatchAndIncrementalLearner<DataType,ResultType>, BatchClusterer<DataType,ClusterType>, BatchCostMinimizationLearner<CostParametersType,ResultType>, BatchLearner<DataType,ResultType>, BayesianEstimator<ObservationType,ParameterType,PosteriorType>, BayesianEstimatorPredictor<ObservationType,ParameterType,PosteriorType>, BayesianParameter<ParameterType,ConditionalType,PriorType>, BayesianRegression<OutputType,PosteriorType>, BinaryCategorizer<InputType>, BinaryConfusionMatrix, BlockExperimentComparison<DataType>, Categorizer<InputType,CategoryType>, ClosedFormComputableDiscreteDistribution<DataType>, ClosedFormComputableDistribution<DataType>, ClosedFormCumulativeDistributionFunction<DomainType>, ClosedFormDifferentiableEvaluator<InputType,OutputType,DerivativeType>, ClosedFormDiscreteUnivariateDistribution<DomainType>, ClosedFormDistribution<DataType>, ClosedFormUnivariateDistribution<NumberType>, Cluster<ClusterType>, ClusterCreator<ClusterType,DataType>, ClusterDivergenceFunction<ClusterType,DataType>, ClusterHierarchyNode<DataType,ClusterType>, ClusterToClusterDivergenceFunction<ClusterType,DataType>, CognitiveModelState, CognitiveModuleFactoryLearner, CognitiveModuleSettings, CognitiveModuleState, Cogxel, CogxelConverter<DataType>, CogxelState, ComputableDistribution<DomainType>, ConfidenceStatistic, ConfidenceWeightedBinaryCategorizer, ConfusionMatrix<CategoryType>, ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType,BeliefType>, ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType,BeliefType>, CostFunction<EvaluatedType,CostParametersType>, CumulativeDistributionFunction<NumberType>, DataDistribution<DataType>, DataDistribution.PMF<KeyType>, DeciderLearner<InputType,OutputType,CategoryType,DeciderType>, DecisionTreeNode<InputType,OutputType>, DiagonalMatrix, DifferentiableCostFunction, DifferentiableEvaluator<InputType,OutputType,DerivativeType>, DifferentiableUnivariateScalarFunction, DifferentiableVectorFunction, DirichletProcessMixtureModel.Updater<ObservationType>, DiscreteDistribution<DataType>, DiscreteTimeFilter<StateType>, DiscriminantBinaryCategorizer<InputType>, DiscriminantCategorizer<InputType,CategoryType,DiscriminantType>, Distribution<DataType>, DistributionEstimator<ObservationType,DistributionType>, DistributionParameter<ParameterType,ConditionalType>, DistributionWeightedEstimator<ObservationType,DistributionType>, DistributionWithMean<DataType>, DivergenceFunction<FirstType,SecondType>, EstimableDistribution<ObservationType,DistributionType>, EuclideanRing<RingType>, Field<FieldType>, FixedClusterInitializer<ClusterType,DataType>, FunctionMinimizer<InputType,OutputType,EvaluatorType>, GradientDescendable, ImportanceSampling.Updater<ObservationType,ParameterType>, IncrementalClusterCreator<ClusterType,DataType>, IncrementalEstimator<DataType,DistributionType,SufficientStatisticsType>, IncrementalLearner<DataType,ResultType>, InfiniteVector<KeyType>, InvertibleCumulativeDistributionFunction<NumberType>, Kernel<InputType>, KernelContainer<InputType>, KernelizableBinaryCategorizerOnlineLearner, KNearestNeighbor<InputType,OutputType>, LinearizableBinaryCategorizerOnlineLearner<InputType>, LineBracketInterpolator<EvaluatorType>, LineMinimizer<EvaluatorType>, LocalTermWeighter, MarkovChainMonteCarlo<ObservationType,ParameterType>, Matrix, Metric<EvaluatedType>, MetropolisHastingsAlgorithm.Updater<ObservationType,ParameterType>, MonteCarloIntegrator<OutputType>, MonteCarloSampler<DataType,SampleType,FunctionType>, MultipleHypothesisComparison<TreatmentData>, MultipleHypothesisComparison.Statistic, MutablePatternRecognizerLite, NearestNeighbor<InputType,OutputType>, NullHypothesisEvaluator<DataType>, ParallelAlgorithm, ParallelizableCostFunction, ParameterAdapter<ObjectType,DataType>, ParameterCostMinimizer<ResultType>, ParameterGradientEvaluator<InputOutputType,GradientType>, ParticleFilter<ObservationType,ParameterType>, ParticleFilter.Updater<ObservationType,ParameterType>, PatternRecognizerLite, PerformanceEvaluator<ObjectType,DataType,ResultType>, Perturber<PerturbedType>, PolynomialFunction.ClosedForm, PrincipalComponentsAnalysis, ProbabilityDensityFunction<DataType>, ProbabilityFunction<DataType>, ProbabilityMassFunction<DataType>, Quaternion, RandomVariable<DataType>, RecursiveBayesianEstimator<ObservationType,ParameterType,BeliefType>, RejectionSampling.Updater<ObservationType,ParameterType>, Ring<RingType>, RootBracketer, RootFinder, Semimetric<InputType>, ShareableCognitiveModuleSettings, SingleTermFilter, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, SufficientStatistic<DataType,DistributionType>, SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType>, SupervisedBatchLearner<InputType,OutputType,ResultType>, SupervisedCostFunction<InputType,TargetType>, SupervisedIncrementalLearner<InputType,OutputType,ResultType>, SupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType>, Term, TermFilter, TermNGram, TermWeightNormalizer, ThresholdBinaryCategorizer<InputType>, Tokenizer, UnivariateDistribution<NumberType>, UnivariateProbabilityDensityFunction, UnivariateScalarFunction, Vector, Vector1D, Vector2D, Vector3D, Vectorizable, VectorizableDifferentiableVectorFunction, VectorizableVectorFunction, VectorSpace<VectorType,EntryType>, VectorThresholdMaximumGainLearner<OutputType>

All Known Implementing Classes:

AbstractAnytimeAlgorithm, AbstractAnytimeBatchLearner, AbstractAnytimeFunctionMinimizer, AbstractAnytimeLineMinimizer, AbstractAnytimeSupervisedBatchLearner, AbstractBaggingLearner, AbstractBatchAndIncrementalLearner, AbstractBatchLearnerContainer, AbstractBaumWelchAlgorithm, AbstractBayesianParameter, AbstractBinaryCategorizer, AbstractBinaryConfusionMatrix, AbstractBracketedRootFinder, AbstractCategorizer, AbstractCharacterBasedTokenizer, AbstractCloneableSerializable, AbstractClosedFormSmoothUnivariateDistribution, AbstractClosedFormUnivariateDistribution, AbstractClusterHierarchyNode, AbstractClusterToClusterDivergenceFunction, AbstractCogxelConverter, AbstractCogxelPairConverter, AbstractConfidenceStatistic, AbstractConfidenceWeightedBinaryCategorizer, AbstractConfusionMatrix, AbstractConjugatePriorBayesianEstimator, AbstractCostFunction, AbstractDataConverter, AbstractDataDistribution, AbstractDecisionTreeLearner, AbstractDecisionTreeNode, AbstractDifferentiableUnivariateScalarFunction, AbstractDiscriminantBinaryCategorizer, AbstractDiscriminantCategorizer, AbstractDistribution, AbstractDocument, AbstractDocumentExtractor, AbstractEntropyBasedGlobalTermWeighter, AbstractEuclideanRing, AbstractField, AbstractField, AbstractFileSerializationHandler, AbstractFrequencyBasedGlobalTermWeighter, AbstractGlobalTermWeighter, AbstractIncrementalEstimator, AbstractInputOutputPair, AbstractIterativeAlgorithm, AbstractIterativeAlgorithmListener, AbstractKalmanFilter, AbstractKernelizableBinaryCategorizerOnlineLearner, AbstractKNearestNeighbor, AbstractLearningExperiment, AbstractLinearCombinationOnlineLearner, AbstractLineBracketInterpolator, AbstractLineBracketInterpolatorPolynomial, AbstractLocalTermWeighter, AbstractMarkovChainMonteCarlo, AbstractMatrix, AbstractMinDistanceFixedClusterInitializer, AbstractMinimizerBasedParameterCostMinimizer, AbstractMTJMatrix, AbstractMTJVector, AbstractMultipleHypothesisComparison, AbstractMultipleHypothesisComparison.Statistic, AbstractMultiTextualConverter, AbstractMutableDoubleMap, AbstractNamed, AbstractNearestNeighbor, AbstractOccurrenceInText, AbstractOnlineBudgetedKernelBinaryCategorizerLearner, AbstractOnlineKernelBinaryCategorizerLearner, AbstractOnlineLinearBinaryCategorizerLearner, AbstractPairwiseMultipleHypothesisComparison, AbstractPairwiseMultipleHypothesisComparison.Statistic, AbstractParallelAlgorithm, AbstractParallelizableCostFunction, AbstractParameterCostMinimizer, AbstractParticleFilter, AbstractPrincipalComponentsAnalysis, AbstractRandomized, AbstractRandomVariable, AbstractRegressor, AbstractRelation, AbstractReverseCachedDataConverter, AbstractReversibleDataConverter, AbstractRing, AbstractRootFinder, AbstractScalarFunction, AbstractScalarMap, AbstractScalarMap.MapWrapper, AbstractSingleDocumentExtractor, AbstractSingleTermFilter, AbstractSingleTextualConverter, AbstractSparseMatrix, AbstractStatefulEvaluator, AbstractStreamSerializationHandler, AbstractSufficientStatistic, AbstractSupervisedBatchAndIncrementalLearner, AbstractSupervisedCostFunction, AbstractSupervisedPerformanceEvaluator, AbstractTargetEstimatePair, AbstractTemporal, AbstractTerm, AbstractTermIndex, AbstractTermWeightNormalizer, AbstractTextSerializationHandler, AbstractTextual, AbstractTextualConverter, AbstractThresholdBinaryCategorizer, AbstractTokenizer, AbstractToVectorEncoder, AbstractUnivariateScalarFunction, AbstractUnweightedEnsemble, AbstractValidationFoldExperiment, AbstractValueDiscriminantPair, AbstractVector, AbstractVectorSpace, AbstractVectorSpaceModel, AbstractVectorThresholdMaximumGainLearner, AbstractWeighted, AbstractWeightedEnsemble, AdaBoost, AdaptiveRegularizationOfWeights, AdaptiveRejectionSampling, AdaptiveRejectionSampling.AbstractEnvelope, AdaptiveRejectionSampling.LineSegment, AdaptiveRejectionSampling.LogEvaluator, AdaptiveRejectionSampling.LowerEnvelope, AdaptiveRejectionSampling.PDFLogEvaluator, AdaptiveRejectionSampling.Point, AdaptiveRejectionSampling.UpperEnvelope, AdditiveEnsemble, AdjustedPValueStatistic, AffinityPropagation, AgglomerativeClusterer, AgglomerativeClusterer.HierarchyNode, AggressiveRelaxedOnlineMaximumMarginAlgorithm, AnalysisOfVarianceOneWay, AnalysisOfVarianceOneWay.Statistic, AnytimeAlgorithmWrapper, AtanFunction, AutoRegressiveMovingAverageFilter, AveragingEnsemble, BaggingCategorizerLearner, BaggingRegressionLearner, BagOfWordsTransform, Ballseptron, BatchMultiPerceptron, BaumWelchAlgorithm, BayesianCredibleInterval, BayesianLinearRegression, BayesianLinearRegression.IncrementalEstimator, BayesianLinearRegression.IncrementalEstimator.SufficientStatistic, BayesianLinearRegression.PredictiveDistribution, BayesianRobustLinearRegression, BayesianRobustLinearRegression.IncrementalEstimator, BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic, BayesianRobustLinearRegression.PredictiveDistribution, BernoulliBayesianEstimator, BernoulliBayesianEstimator.Parameter, BernoulliConfidence, BernoulliDistribution, BernoulliDistribution.CDF, BernoulliDistribution.PMF, BetaBinomialDistribution, BetaBinomialDistribution.CDF, BetaBinomialDistribution.MomentMatchingEstimator, BetaBinomialDistribution.PMF, BetaDistribution, BetaDistribution.CDF, BetaDistribution.MomentMatchingEstimator, BetaDistribution.PDF, BetaDistribution.WeightedMomentMatchingEstimator, BinaryBaggingLearner, BinaryCategorizerSelector, BinaryClusterHierarchyNode, BinaryLocalTermWeighter, BinaryVersusCategorizer, BinaryVersusCategorizer.Learner, BinomialBayesianEstimator, BinomialBayesianEstimator.Parameter, BinomialDistribution, BinomialDistribution.CDF, BinomialDistribution.MaximumLikelihoodEstimator, BinomialDistribution.PMF, BonferroniCorrection, BooleanActivatableCogxel, CategoricalDistribution, CategoricalDistribution.PMF, CategorizationTree, CategorizationTreeLearner, CategorizationTreeNode, CategoryBalancedBaggingLearner, CategoryBalancedIVotingLearner, CauchyDistribution, CauchyDistribution.CDF, CauchyDistribution.PDF, CentroidCluster, CentroidClusterDivergenceFunction, ChebyshevDistanceMetric, ChebyshevInequality, ChineseRestaurantProcess, ChineseRestaurantProcess.PMF, ChiSquareConfidence, ChiSquareConfidence.Statistic, ChiSquareDistribution, ChiSquareDistribution.CDF, ChiSquareDistribution.PDF, CholeskyDecompositionMTJ, ClusterCentroidDivergenceFunction, ClusterCompleteLinkDivergenceFunction, ClusterDistortionMeasure, ClusterMeanLinkDivergenceFunction, ClusterSingleLinkDivergenceFunction, CognitiveModelLiteState, CognitiveModuleStateWrapper, CogxelBooleanConverter, CogxelDoubleConverter, CogxelInputOutputPairConverter, CogxelMatrixConverter, CogxelStateLite, CogxelTargetEstimatePairConverter, CogxelVectorCollectionConverter, CogxelVectorConverter, CogxelWeightedInputOutputPairConverter, ComplexNumber, CompositeBatchLearnerPair, CompositeCategorizer, CompositeEvaluatorList, CompositeEvaluatorPair, CompositeEvaluatorTriple, CompositeLocalGlobalTermWeighter, ConfidenceInterval, ConfidenceWeightedDiagonalDeviation, ConfidenceWeightedDiagonalDeviationProject, ConfidenceWeightedDiagonalVariance, ConfidenceWeightedDiagonalVarianceProject, ConfusionMatrixPerformanceEvaluator, ConstantEvaluator, ConstantLearner, ConvexReceiverOperatingCharacteristic, CosineDistanceMetric, CosineFunction, CosineSimilarityFunction, CrossFoldCreator, DataCountTreeSetBinnedMapHistogram, DecisionTree, DefaultBayesianParameter, DefaultBinaryConfusionMatrix, DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer, DefaultBinaryConfusionMatrix.CombineSummarizer, DefaultBinaryConfusionMatrix.PerformanceEvaluator, DefaultBinaryConfusionMatrixConfidenceInterval.Summary, DefaultBooleanToNumberConverter, DefaultBooleanToNumberConverter.Reverse, DefaultCluster, DefaultClusterCreator, DefaultClusterHierarchyNode, DefaultCogxel, DefaultComparator, DefaultConfidenceWeightedBinaryCategorizer, DefaultConfusionMatrix, DefaultConfusionMatrix.ActualPredictedPairSummarizer, DefaultConfusionMatrix.CombineSummarizer, DefaultConfusionMatrix.Factory, DefaultDataDistribution, DefaultDataDistribution.DefaultFactory, DefaultDataDistribution.Estimator, DefaultDataDistribution.PMF, DefaultDataDistribution.WeightedEstimator, DefaultDateField, DefaultDistributionParameter, DefaultDivergenceFunctionContainer, DefaultDocument, DefaultDuration, DefaultFactory, DefaultIdentifiedValue, DefaultIncrementalClusterCreator, DefaultIndexedTerm, DefaultIndexer, DefaultInfiniteVector, DefaultInputOutputPair, DefaultKernelBinaryCategorizer, DefaultKernelContainer, DefaultKernelsContainer, DefaultKeyValuePair, DefaultNamedValue, DefaultPair, DefaultPrecisionRecallPair, DefaultSemanticIdentifierMap, DefaultStopList, DefaultTargetEstimatePair, DefaultTemporalValue, DefaultTerm, DefaultTermCounts, DefaultTermIndex, DefaultTermNGram, DefaultTermOccurrence, DefaultTextField, DefaultTextual, DefaultToken, DefaultTriple, DefaultValueDiscriminantPair, DefaultVectorFactoryContainer, DefaultWeightedInputOutputPair, DefaultWeightedPair, DefaultWeightedTargetEstimatePair, DefaultWeightedValue, DefaultWeightedValue.WeightComparator, DefaultWeightedValueDiscriminant, DelayFunction, DenseMatrix, DenseVector, DeterministicDistribution, DeterministicDistribution.CDF, DeterministicDistribution.PMF, DiagonalConfidenceWeightedBinaryCategorizer, DiagonalMatrixMTJ, DictionaryFilter, DifferentiableFeedforwardNeuralNetwork, DifferentiableGeneralizedLinearModel, DirectionalVectorToDifferentiableScalarFunction, DirectionalVectorToScalarFunction, DirectSampler, DirichletDistribution, DirichletDistribution.PDF, DirichletProcessClustering, DirichletProcessMixtureModel, DirichletProcessMixtureModel.DPMMCluster, DirichletProcessMixtureModel.DPMMLogConditional, DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater, DirichletProcessMixtureModel.MultivariateMeanUpdater, DirichletProcessMixtureModel.Sample, DiscreteNaiveBayesCategorizer, DiscreteNaiveBayesCategorizer.Learner, DistanceSamplingClusterInitializer, DistributionParameterEstimator, DistributionParameterEstimator.DistributionWrapper, DivergencesEvaluator, DivergencesEvaluator.Learner, DocumentFieldConcatenator, DocumentSingleFieldConverter, DominanceGlobalTermWeighter, DynamicArrayMap, EigenvectorPowerIteration, ElementWiseDifferentiableVectorFunction, ElementWiseVectorFunction, EntropyEvaluator, EntropyGlobalTermWeighter, EuclideanDistanceCostFunction, EuclideanDistanceMetric, EuclideanDistanceSquaredMetric, EvaluatorBasedCognitiveModuleFactory, EvaluatorBasedCognitiveModuleFactoryLearner, EvaluatorBasedCognitiveModuleSettings, EvaluatorToCategorizerAdapter, EvaluatorToCategorizerAdapter.Learner, ExponentialBayesianEstimator, ExponentialBayesianEstimator.Parameter, ExponentialDistribution, ExponentialDistribution.CDF, ExponentialDistribution.MaximumLikelihoodEstimator, ExponentialDistribution.PDF, ExponentialDistribution.WeightedMaximumLikelihoodEstimator, ExponentialKernel, ExtendedKalmanFilter, FeedforwardNeuralNetwork, FieldConfidenceInterval, FiniteCapacityBuffer, FisherLinearDiscriminantBinaryCategorizer, FisherLinearDiscriminantBinaryCategorizer.ClosedFormSolver, FisherSignConfidence, FisherSignConfidence.Statistic, FletcherXuHybridEstimation, Forgetron, Forgetron.Basic, Forgetron.Greedy, Forgetron.Result, ForwardReverseEvaluatorPair, FourierTransform, FourierTransform.Inverse, FriedmanConfidence, FriedmanConfidence.Statistic, FunctionMinimizerBFGS, FunctionMinimizerConjugateGradient, FunctionMinimizerDFP, FunctionMinimizerDirectionSetPowell, FunctionMinimizerFletcherReeves, FunctionMinimizerGradientDescent, FunctionMinimizerLiuStorey, FunctionMinimizerNelderMead, FunctionMinimizerPolakRibiere, FunctionMinimizerQuasiNewton, GammaDistribution, GammaDistribution.CDF, GammaDistribution.MomentMatchingEstimator, GammaDistribution.PDF, GammaDistribution.WeightedMomentMatchingEstimator, GammaInverseScaleBayesianEstimator, GammaInverseScaleBayesianEstimator.Parameter, GaussianCluster, GaussianClusterCreator, GaussianClusterDivergenceFunction, GaussianConfidence, GaussianConfidence.Statistic, GaussianContextRecognizer, GaussianContextRecognizer.Learner, GaussianProcessRegression, GaussianProcessRegression.PredictiveDistribution, GaussNewtonAlgorithm, GeneralizedHebbianAlgorithm, GeneralizedLinearModel, GeneticAlgorithm, GeometricDistribution, GeometricDistribution.CDF, GeometricDistribution.MaximumLikelihoodEstimator, GeometricDistribution.PMF, GradientDescendableApproximator, GreedyClusterInitializer, GZIPSerializationHandler, HiddenMarkovModel, HolmCorrection, HolmCorrection.Statistic, IdentityDataConverter, IdentityDistanceMetric, IdentityEvaluator, IdentityLearner, IdentityScalarFunction, ImportanceSampler, ImportanceSampling, ImportanceSampling.DefaultUpdater, IndexedTermSimilarityRelation, InputOutputSlopeTriplet, InputOutputTransformedBatchLearner, IntegerSpan, InverseDocumentFrequencyGlobalTermWeighter, InverseGammaDistribution, InverseGammaDistribution.CDF, InverseGammaDistribution.PDF, InverseWishartDistribution, InverseWishartDistribution.PDF, IterationMeasurablePerformanceReporter, IterationStartReporter, IVotingCategorizerLearner, IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria, JavaDefaultBinarySerializationHandler, KalmanFilter, KDTree, KDTree.Neighborhood.Neighbor, KDTree.PairFirstVectorizableIndexComparator, KernelAdatron, KernelBasedIterativeRegression, KernelBinaryCategorizer, KernelBinaryCategorizerOnlineLearnerAdapter, KernelDistanceMetric, KernelPerceptron, KernelPrincipalComponentsAnalysis, KernelPrincipalComponentsAnalysis.Function, KernelScalarFunction, KernelWeightedRobustRegression, KMeansClusterer, KMeansClustererWithRemoval, KMeansFactory, KNearestNeighborExhaustive, KNearestNeighborExhaustive.Learner, KNearestNeighborExhaustive.Neighbor, KNearestNeighborKDTree, KNearestNeighborKDTree.Learner, KolmogorovDistribution, KolmogorovDistribution.CDF, KolmogorovSmirnovConfidence, KolmogorovSmirnovConfidence.Statistic, KolmogorovSmirnovDivergence, KolmogorovSmirnovEvaluator, LaplaceDistribution, LaplaceDistribution.CDF, LaplaceDistribution.MaximumLikelihoodEstimator, LaplaceDistribution.PDF, LaplaceDistribution.WeightedMaximumLikelihoodEstimator, LatentDirichletAllocationVectorGibbsSampler, LatentDirichletAllocationVectorGibbsSampler.Result, LatentSemanticAnalysis, LatentSemanticAnalysis.Transform, LearnerComparisonExperiment, LearnerRepeatExperiment, LearnerValidationExperiment, LeastSquaresEstimator, LentzMethod, LetterNumberTokenizer, LevenbergMarquardtEstimation, LinearBasisRegression, LinearBinaryCategorizer, LinearCombinationFunction, LinearCombinationScalarFunction, LinearCombinationVectorFunction, LinearDiscriminant, LinearDiscriminantWithBias, LinearDynamicalSystem, LinearFunction, LinearKernel, LinearMixtureModel, LinearMultiCategorizer, LinearRegression, LinearRegression.Statistic, LinearRegressionCoefficientExtractor, LinearVectorFunction, LinearVectorScalarFunction, LineBracket, LineBracketInterpolatorBrent, LineBracketInterpolatorGoldenSection, LineBracketInterpolatorHermiteCubic, LineBracketInterpolatorHermiteParabola, LineBracketInterpolatorLinear, LineBracketInterpolatorParabola, LineMinimizerBacktracking, LineMinimizerDerivativeBased, LineMinimizerDerivativeBased.InternalFunction, LineMinimizerDerivativeFree, LocallyWeightedFunction.Learner, LocallyWeightedKernelScalarFunction, LogisticDistribution, LogisticDistribution.CDF, LogisticDistribution.PDF, LogisticRegression, LogisticRegression.Function, LogLocalTermWeighter, LogNormalDistribution, LogNormalDistribution.CDF, LogNormalDistribution.MaximumLikelihoodEstimator, LogNormalDistribution.PDF, LogNormalDistribution.WeightedMaximumLikelihoodEstimator, LogNumber, LowerCaseTermFilter, ManhattanDistanceMetric, MannWhitneyUConfidence, MannWhitneyUConfidence.Statistic, MarkovChain, MarkovInequality, MaximumAPosterioriCategorizer, MaximumAPosterioriCategorizer.Learner, MaximumLikelihoodDistributionEstimator, MaximumLikelihoodDistributionEstimator.DistributionEstimationTask, MeanAbsoluteErrorEvaluator, MeanL1CostFunction, MeanLearner, MeanSquaredErrorCostFunction, MeanSquaredErrorEvaluator, MeanZeroOneErrorEvaluator, MedoidClusterCreator, MetropolisHastingsAlgorithm, MinimizerBasedRootFinder, MinkowskiDistanceMetric, MixtureOfGaussians.EMLearner, MixtureOfGaussians.Learner, MixtureOfGaussians.PDF, MostFrequentLearner, MostFrequentSummarizer, MovingAverageFilter, MultiCategoryAdaBoost, MultinomialBayesianEstimator, MultinomialBayesianEstimator.Parameter, MultinomialDistribution, MultinomialDistribution.Domain.MultinomialIterator, MultinomialDistribution.PMF, MultipleComparisonExperiment, MultipleComparisonExperiment.Statistic, MultivariateDecorrelator, MultivariateDecorrelator.DiagonalCovarianceLearner, MultivariateDecorrelator.FullCovarianceLearner, MultivariateDiscriminant, MultivariateDiscriminantWithBias, MultivariateGaussian, MultivariateGaussian.IncrementalEstimator, MultivariateGaussian.IncrementalEstimatorCovarianceInverse, MultivariateGaussian.MaximumLikelihoodEstimator, MultivariateGaussian.PDF, MultivariateGaussian.SufficientStatistic, MultivariateGaussian.SufficientStatisticCovarianceInverse, MultivariateGaussian.WeightedMaximumLikelihoodEstimator, MultivariateGaussianInverseGammaDistribution, MultivariateGaussianMeanBayesianEstimator, MultivariateGaussianMeanBayesianEstimator.Parameter, MultivariateGaussianMeanCovarianceBayesianEstimator, MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter, MultivariateLinearRegression, MultivariateMixtureDensityModel, MultivariateMixtureDensityModel.PDF, MultivariateMonteCarloIntegrator, MultivariatePolyaDistribution, MultivariatePolyaDistribution.PMF, MultivariateStudentTDistribution, MultivariateStudentTDistribution.PDF, MutableDouble, MutableInteger, MutableLong, NearestNeighborExhaustive, NearestNeighborExhaustive.Learner, NearestNeighborKDTree, NearestNeighborKDTree.Learner, NegativeBinomialDistribution, NegativeBinomialDistribution.CDF, NegativeBinomialDistribution.MaximumLikelihoodEstimator, NegativeBinomialDistribution.PMF, NegativeBinomialDistribution.WeightedMaximumLikelihoodEstimator, NegativeLogLikelihood, NeighborhoodGaussianClusterInitializer, NemenyiConfidence, NemenyiConfidence.Statistic, NGramFilter, NormalInverseGammaDistribution, NormalInverseGammaDistribution.PDF, NormalInverseWishartDistribution, NormalInverseWishartDistribution.PDF, NormalizedKernel, NormalizedLogLocalTermWeighter, NumberAverager, NumberComparator, NumberConverterToVectorAdapter, NumberToVectorEncoder, NumericalDifferentiator, NumericalDifferentiator.DoubleJacobian, NumericalDifferentiator.MatrixJacobian, NumericalDifferentiator.VectorJacobian, ObjectToStringConverter, ObjectToStringTextualConverter, OnlineBaggingCategorizerLearner, OnlineBinaryMarginInfusedRelaxedAlgorithm, OnlineKernelPerceptron, OnlineKernelRandomizedBudgetPerceptron, OnlineLearnerValidationExperiment, OnlineMultiPerceptron, OnlineMultiPerceptron.ProportionalUpdate, OnlineMultiPerceptron.UniformUpdate, OnlinePassiveAggressivePerceptron, OnlinePassiveAggressivePerceptron.AbstractSoftMargin, OnlinePassiveAggressivePerceptron.LinearSoftMargin, OnlinePassiveAggressivePerceptron.QuadraticSoftMargin, OnlinePerceptron, OnlineRampPassiveAggressivePerceptron, OnlineShiftingPerceptron, OnlineShiftingPerceptron.LinearResult, OnlineVotedPerceptron, OptimizedKMeansClusterer, ParallelBaumWelchAlgorithm, ParallelBaumWelchAlgorithm.DistributionEstimatorTask, ParallelClusterDistortionMeasure, ParallelDirichletProcessMixtureModel, ParallelDirichletProcessMixtureModel.ClusterUpdaterTask, ParallelDirichletProcessMixtureModel.ObservationAssignmentTask, ParallelHiddenMarkovModel, ParallelHiddenMarkovModel.ComputeTransitionsTask, ParallelHiddenMarkovModel.LogLikelihoodTask, ParallelHiddenMarkovModel.NormalizeTransitionTask, ParallelHiddenMarkovModel.ObservationLikelihoodTask, ParallelHiddenMarkovModel.StateObservationLikelihoodTask, ParallelHiddenMarkovModel.ViterbiTask, ParallelizedCostFunctionContainer, ParallelizedGeneticAlgorithm, ParallelizedKMeansClusterer, ParallelLatentDirichletAllocationVectorGibbsSampler, ParallelLatentDirichletAllocationVectorGibbsSampler.DocumentSampleTask, ParallelLearnerValidationExperiment, ParallelNegativeLogLikelihood, ParameterAdaptableBatchLearnerWrapper, ParameterDerivativeFreeCostMinimizer, ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree, ParameterDifferentiableCostMinimizer, ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased, ParetoDistribution, ParetoDistribution.CDF, ParetoDistribution.PDF, PartitionalClusterer, Perceptron, PIDController, PIDController.State, PoissonBayesianEstimator, PoissonBayesianEstimator.Parameter, PoissonDistribution, PoissonDistribution.CDF, PoissonDistribution.MaximumLikelihoodEstimator, PoissonDistribution.PMF, PoissonDistribution.WeightedMaximumLikelihoodEstimator, PolynomialFunction, PolynomialFunction.Cubic, PolynomialFunction.Linear, PolynomialFunction.Quadratic, PolynomialFunction.Regression, PolynomialKernel, PorterEnglishStemmingFilter, PrimalEstimatedSubGradient, PrincipalComponentsAnalysisFunction, ProbabilisticLatentSemanticAnalysis, ProbabilisticLatentSemanticAnalysis.Result, ProbabilisticLatentSemanticAnalysis.StatusPrinter, ProductKernel, Projectron, Projectron.LinearSoftMargin, PrototypeFactory, Quadtree, Quadtree.Node, RadialBasisKernel, RandomByTwoFoldCreator, RandomDataPartitioner, RandomSubspace, RandomSubVectorThresholdLearner, ReceiverOperatingCharacteristic, ReceiverOperatingCharacteristic.DataPoint, ReceiverOperatingCharacteristic.DataPoint.Sorter, ReceiverOperatingCharacteristic.Statistic, RegressionTree, RegressionTreeLearner, RegressionTreeNode, RejectionSampling, RejectionSampling.DefaultUpdater, RelaxedOnlineMaximumMarginAlgorithm, RemoveOldestKernelPerceptron, RingAverager, RootBracketExpander, RootFinderBisectionMethod, RootFinderFalsePositionMethod, RootFinderNewtonsMethod, RootFinderRiddersMethod, RootFinderSecantMethod, RootMeanSquaredErrorEvaluator, SamplingImportanceResamplingParticleFilter, ScalarBasisSet, ScalarDataDistribution, ScalarDataDistribution.CDF, ScalarDataDistribution.Estimator, ScalarDataDistribution.PMF, ScalarFunctionKernel, ScalarFunctionToBinaryCategorizerAdapter, ScalarMixtureDensityModel, ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.EMLearner, ScalarMixtureDensityModel.PDF, ScalarThresholdBinaryCategorizer, SequencePredictionLearner, SequentialMinimalOptimization, ShafferStaticCorrection, ShafferStaticCorrection.Statistic, SharedSemanticMemoryLiteFactory, SharedSemanticMemoryLiteSettings, SidakCorrection, SigmoidFunction, SigmoidKernel, SimplePatternRecognizer, SimplePatternRecognizerState, SimpleStatisticalSpellingCorrector, SimpleStatisticalSpellingCorrector.Learner, SimulatedAnnealer, SingleToMultiTextualConverterAdapter, SnedecorFDistribution, SnedecorFDistribution.CDF, SolverFunction, SparseColumnMatrix, SparseMatrix, SparseRowMatrix, SparseVector, StandardDistributionNormalizer, StandardDistributionNormalizer.Learner, StopListFilter, Stoptron, StringEvaluatorSingleTermFilter, StringToDoubleConverter, StringToIntegerConverter, StudentizedRangeDistribution, StudentizedRangeDistribution.CDF, StudentTConfidence, StudentTConfidence.Statistic, StudentTConfidence.Summary, StudentTDistribution, StudentTDistribution.CDF, StudentTDistribution.MaximumLikelihoodEstimator, StudentTDistribution.PDF, StudentTDistribution.WeightedMaximumLikelihoodEstimator, SubVectorEvaluator, SuccessiveOverrelaxation, SuccessiveOverrelaxation.Entry, SumKernel, SumSquaredErrorCostFunction, SumSquaredErrorCostFunction.Cache, SumSquaredErrorCostFunction.GradientPartialSSE, SupervisedLearnerComparisonExperiment, SupervisedLearnerValidationExperiment, SynonymFilter, TermFrequencyLocalTermWeighter, TermLengthFilter, TermVectorSimilarityNetworkCreator, TextDocumentExtractor, ThinSingularValueDecomposition, ThreeLayerFeedforwardNeuralNetwork, ThresholdFunction, TimeSeriesPredictionLearner, TreeSetBinner, TukeyKramerConfidence, TukeyKramerConfidence.Statistic, UniformDistribution, UniformDistribution.CDF, UniformDistribution.MaximumLikelihoodEstimator, UniformDistribution.PDF, UniformDistributionBayesianEstimator, UniformDistributionBayesianEstimator.Parameter, UniqueBooleanVectorEncoder, UnitTermWeightNormalizer, UnivariateGaussian, UnivariateGaussian.CDF, UnivariateGaussian.CDF.Inverse, UnivariateGaussian.ErrorFunction, UnivariateGaussian.ErrorFunction.Inverse, UnivariateGaussian.IncrementalEstimator, UnivariateGaussian.MaximumLikelihoodEstimator, UnivariateGaussian.PDF, UnivariateGaussian.SufficientStatistic, UnivariateGaussian.WeightedMaximumLikelihoodEstimator, UnivariateGaussianMeanBayesianEstimator, UnivariateGaussianMeanBayesianEstimator.Parameter, UnivariateGaussianMeanVarianceBayesianEstimator, UnivariateGaussianMeanVarianceBayesianEstimator.Parameter, UnivariateLinearRegression, UnivariateMonteCarloIntegrator, UnivariateRandomVariable, UnivariateSummaryStatistics, UnsignedLogNumber, ValueClamper, ValueMapper, Vector1, Vector2, Vector3, VectorBasedCognitiveModelInput, VectorElementThresholdCategorizer, VectorEntryFunction, VectorFunctionKernel, VectorFunctionLinearDiscriminant, VectorFunctionToScalarFunction, VectorFunctionToScalarFunction.Learner, VectorizableCrossoverFunction, VectorizableIndexComparator, VectorizablePerturber, VectorizableVectorConverter, VectorizableVectorConverterWithBias, VectorMeanCentroidClusterCreator, VectorNaiveBayesCategorizer, VectorNaiveBayesCategorizer.BatchGaussianLearner, VectorNaiveBayesCategorizer.Learner, VectorNaiveBayesCategorizer.OnlineLearner, VectorThresholdGiniImpurityLearner, VectorThresholdHellingerDistanceLearner, VectorThresholdInformationGainLearner, VectorThresholdVarianceLearner, VotingCategorizerEnsemble, WeibullDistribution, WeibullDistribution.CDF, WeibullDistribution.PDF, WeightedAdditiveEnsemble, WeightedAveragingEnsemble, WeightedBinaryEnsemble, WeightedEuclideanDistanceMetric, WeightedKernel, WeightedMeanLearner, WeightedMostFrequentLearner, WeightedNumberAverager, WeightedRingAverager, WeightedVotingCategorizerEnsemble, WilcoxonSignedRankConfidence, WilcoxonSignedRankConfidence.Statistic, WinnerTakeAllCategorizer, WinnerTakeAllCategorizer.Learner, Winnow, WolfeConditions, XStreamSerializationHandler, YuleSimonDistribution, YuleSimonDistribution.CDF, YuleSimonDistribution.PMF, ZeroKernel

@CodeReviews(reviews={@CodeReview(reviewer="Kevin R. Dixon",date="2008-10-02",changesNeeded=false,comments="Looks fine."),@CodeReview(reviewer="Kevin R. Dixon",date="2007-11-25",changesNeeded=false,comments="Looks fine.")})
public interface CloneableSerializable
extends Cloneable, Serializable

An object that is both cloneable and serializable, because Java's Cloneable interface mistakenly doesn't have a clone() method (search on the Web, it's funny "lost in the mists of time..." )

Since:

1.0

Author:

Kevin R. Dixon

Method Summary

CloneableSerializable

clone() Creates a new clone (shallow copy) of this object.

Method Detail

clone

CloneableSerializable clone()

Creates a new clone (shallow copy) of this object.

Returns:

A new clone (shallow copy) of this object.