gov.sandia.cognition.evaluator
Interface Evaluator<InputType,OutputType>

Type Parameters:
InputType - The type of the input the evaluator can use.
OutputType - The type of the output the evaluator will produce.
All Known Subinterfaces:
BinaryCategorizer<InputType>, Categorizer<InputType,CategoryType>, ClosedFormCumulativeDistributionFunction<DomainType>, ClosedFormDifferentiableEvaluator<InputType,OutputType,DerivativeType>, ConfidenceWeightedBinaryCategorizer, CostFunction<EvaluatedType,CostParametersType>, CumulativeDistributionFunction<NumberType>, DataConverter<InputType,OutputType>, DataDistribution.PMF<KeyType>, DataToVectorEncoder<InputType>, DifferentiableCostFunction, DifferentiableEvaluator<InputType,OutputType,DerivativeType>, DifferentiableUnivariateScalarFunction, DifferentiableVectorFunction, DiscreteTimeFilter<StateType>, DiscriminantBinaryCategorizer<InputType>, DiscriminantCategorizer<InputType,CategoryType,DiscriminantType>, GradientDescendable, InvertibleCumulativeDistributionFunction<NumberType>, KNearestNeighbor<InputType,OutputType>, MultiTextualConverter<InputType,OutputType>, NearestNeighbor<InputType,OutputType>, ParallelizableCostFunction, ParameterGradientEvaluator<InputOutputType,GradientType>, PolynomialFunction.ClosedForm, ProbabilityDensityFunction<DataType>, ProbabilityFunction<DataType>, ProbabilityMassFunction<DataType>, Regressor<InputType>, ReversibleDataConverter<InputType,OutputType>, ReversibleEvaluator<InputType,OutputType,ReverseType>, ScalarFunction<InputType>, SingleTextualConverter<InputType,OutputType>, SmoothCumulativeDistributionFunction, StatefulEvaluator<InputType,OutputType,StateType>, SupervisedCostFunction<InputType,TargetType>, ThresholdBinaryCategorizer<InputType>, UnivariateProbabilityDensityFunction, UnivariateScalarFunction, VectorFunction, VectorInputEvaluator<InputType,OutputType>, VectorizableDifferentiableVectorFunction, VectorizableVectorFunction, VectorOutputEvaluator<InputType,OutputType>
All Known Implementing Classes:
AbstractBinaryCategorizer, AbstractCategorizer, AbstractConfidenceWeightedBinaryCategorizer, AbstractCostFunction, AbstractDataConverter, AbstractDifferentiableUnivariateScalarFunction, AbstractDiscriminantBinaryCategorizer, AbstractDiscriminantCategorizer, AbstractKNearestNeighbor, AbstractMultiTextualConverter, AbstractNearestNeighbor, AbstractParallelizableCostFunction, AbstractRegressor, AbstractReverseCachedDataConverter, AbstractReversibleDataConverter, AbstractScalarFunction, AbstractSingleTextualConverter, AbstractStatefulEvaluator, AbstractSupervisedCostFunction, AbstractThresholdBinaryCategorizer, AbstractToVectorEncoder, AbstractUnivariateScalarFunction, AdaptiveRejectionSampling.AbstractEnvelope, AdaptiveRejectionSampling.LineSegment, AdaptiveRejectionSampling.LogEvaluator, AdaptiveRejectionSampling.LowerEnvelope, AdaptiveRejectionSampling.PDFLogEvaluator, AdaptiveRejectionSampling.UpperEnvelope, AdditiveEnsemble, AtanFunction, AutoRegressiveMovingAverageFilter, AveragingEnsemble, BagOfWordsTransform, BayesianLinearRegression.PredictiveDistribution, BayesianRobustLinearRegression.PredictiveDistribution, BernoulliDistribution.CDF, BernoulliDistribution.PMF, BetaBinomialDistribution.CDF, BetaBinomialDistribution.PMF, BetaDistribution.CDF, BetaDistribution.PDF, BinaryVersusCategorizer, BinomialDistribution.CDF, BinomialDistribution.PMF, CategoricalDistribution.PMF, CategorizationTree, CauchyDistribution.CDF, CauchyDistribution.PDF, ChineseRestaurantProcess.PMF, ChiSquareDistribution.CDF, ChiSquareDistribution.PDF, ClusterDistortionMeasure, CompositeCategorizer, CompositeEvaluatorList, CompositeEvaluatorPair, CompositeEvaluatorTriple, CompositeLocalGlobalTermWeighter, ConstantEvaluator, ConvexReceiverOperatingCharacteristic, CosineFunction, DecisionTree, DefaultBooleanToNumberConverter, DefaultBooleanToNumberConverter.Reverse, DefaultConfidenceWeightedBinaryCategorizer, DefaultDataDistribution.PMF, DefaultKernelBinaryCategorizer, DelayFunction, DeterministicDistribution.CDF, DeterministicDistribution.PMF, DiagonalConfidenceWeightedBinaryCategorizer, DifferentiableFeedforwardNeuralNetwork, DifferentiableGeneralizedLinearModel, DirectionalVectorToDifferentiableScalarFunction, DirectionalVectorToScalarFunction, DirichletDistribution.PDF, DiscreteNaiveBayesCategorizer, DistributionParameterEstimator.DistributionWrapper, DivergencesEvaluator, DocumentFieldConcatenator, DocumentSingleFieldConverter, ElementWiseDifferentiableVectorFunction, ElementWiseVectorFunction, EntropyEvaluator, EuclideanDistanceCostFunction, EvaluatorToCategorizerAdapter, ExponentialDistribution.CDF, ExponentialDistribution.PDF, ExtendedKalmanFilter.ModelJacobianEvaluator, FeedforwardNeuralNetwork, FisherLinearDiscriminantBinaryCategorizer, Forgetron.Result, ForwardReverseEvaluatorPair, FourierTransform, FourierTransform.Inverse, GammaDistribution.CDF, GammaDistribution.PDF, GaussianContextRecognizer, GaussianProcessRegression.PredictiveDistribution, GeneralizedLinearModel, GeometricDistribution.CDF, GeometricDistribution.PMF, GradientDescendableApproximator, IdentityDataConverter, IdentityEvaluator, IdentityScalarFunction, InverseGammaDistribution.CDF, InverseGammaDistribution.PDF, InverseWishartDistribution.PDF, KernelBinaryCategorizer, KernelPrincipalComponentsAnalysis.Function, KernelScalarFunction, KNearestNeighborExhaustive, KNearestNeighborExhaustive.Learner, KNearestNeighborKDTree, KNearestNeighborKDTree.Learner, KolmogorovDistribution.CDF, KolmogorovSmirnovDivergence, KolmogorovSmirnovEvaluator, LaplaceDistribution.CDF, LaplaceDistribution.PDF, LatentSemanticAnalysis.Transform, LinearBinaryCategorizer, LinearCombinationFunction, LinearCombinationScalarFunction, LinearCombinationVectorFunction, LinearDiscriminant, LinearDiscriminantWithBias, LinearDynamicalSystem, LinearFunction, LinearMultiCategorizer, LinearRegressionCoefficientExtractor, LinearVectorFunction, LinearVectorScalarFunction, LineMinimizerDerivativeBased.InternalFunction, LocallyWeightedFunction, LocallyWeightedKernelScalarFunction, LogisticDistribution.CDF, LogisticDistribution.PDF, LogisticRegression.Function, LogNormalDistribution.CDF, LogNormalDistribution.PDF, MaximumAPosterioriCategorizer, MeanL1CostFunction, MeanSquaredErrorCostFunction, MeanZeroOneErrorEvaluator, MixtureOfGaussians.PDF, MovingAverageFilter, MultinomialDistribution.PMF, MultivariateDecorrelator, MultivariateDiscriminant, MultivariateDiscriminantWithBias, MultivariateGaussian.PDF, MultivariateMixtureDensityModel.PDF, MultivariatePolyaDistribution.PMF, MultivariateStudentTDistribution.PDF, NearestNeighborExhaustive, NearestNeighborKDTree, NearestNeighborKDTree.Learner, NegativeBinomialDistribution.CDF, NegativeBinomialDistribution.PMF, NegativeLogLikelihood, NormalInverseGammaDistribution.PDF, NormalInverseWishartDistribution.PDF, NumberConverterToVectorAdapter, NumberToVectorEncoder, NumericalDifferentiator, NumericalDifferentiator.DoubleJacobian, NumericalDifferentiator.MatrixJacobian, NumericalDifferentiator.VectorJacobian, ObjectToStringConverter, ObjectToStringTextualConverter, OnlineShiftingPerceptron.LinearResult, ParallelClusterDistortionMeasure, ParallelizedCostFunctionContainer, ParallelNegativeLogLikelihood, ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree, ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased, ParetoDistribution.CDF, ParetoDistribution.PDF, PIDController, PoissonDistribution.CDF, PoissonDistribution.PMF, PolynomialFunction, PolynomialFunction.Cubic, PolynomialFunction.Linear, PolynomialFunction.Quadratic, PrincipalComponentsAnalysisFunction, ProbabilisticLatentSemanticAnalysis.Result, ReceiverOperatingCharacteristic, RegressionTree, RejectionSampling.ScalarEstimator.MinimizerFunction, ScalarBasisSet, ScalarDataDistribution.CDF, ScalarDataDistribution.PMF, ScalarFunctionToBinaryCategorizerAdapter, ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.PDF, ScalarThresholdBinaryCategorizer, SigmoidFunction, SimpleStatisticalSpellingCorrector, SingleToMultiTextualConverterAdapter, SnedecorFDistribution.CDF, SolverFunction, StandardDistributionNormalizer, StringToDoubleConverter, StringToIntegerConverter, StudentizedRangeDistribution.CDF, StudentTDistribution.CDF, StudentTDistribution.PDF, SubVectorEvaluator, SumSquaredErrorCostFunction, ThreeLayerFeedforwardNeuralNetwork, ThresholdFunction, UniformDistribution.CDF, UniformDistribution.PDF, UniqueBooleanVectorEncoder, UnivariateGaussian.CDF, UnivariateGaussian.CDF.Inverse, UnivariateGaussian.ErrorFunction, UnivariateGaussian.ErrorFunction.Inverse, UnivariateGaussian.PDF, ValueClamper, ValueMapper, VectorElementThresholdCategorizer, VectorEntryFunction, VectorFunctionLinearDiscriminant, VectorFunctionToScalarFunction, VectorizableVectorConverter, VectorizableVectorConverterWithBias, VectorNaiveBayesCategorizer, VotingCategorizerEnsemble, WeibullDistribution.CDF, WeibullDistribution.PDF, WeightedAdditiveEnsemble, WeightedAveragingEnsemble, WeightedBinaryEnsemble, WeightedVotingCategorizerEnsemble, WinnerTakeAllCategorizer, YuleSimonDistribution.CDF, YuleSimonDistribution.PMF

@CodeReviews(reviews={@CodeReview(reviewer="Kevin R. Dixon",date="2008-02-08",changesNeeded=false,comments="Looks fine."),@CodeReview(reviewer="Jonathan McClain",date="2006-05-16",changesNeeded=false,comments="Interface looks good.")})
public interface Evaluator<InputType,OutputType>

The Evaluator interface is a general interface to a function that can take an input and produce an output. It can be treated as a either a means of creating simple "delegate" type objects in Java or it can be treated as a "black box" component to provide some functionality.

Since:
1.0
Author:
Justin Basilico
See Also:
StatefulEvaluator

Method Summary
 OutputType evaluate(InputType input)
          Evaluates the function on the given input and returns the output.
 

Method Detail

evaluate

OutputType evaluate(InputType input)
Evaluates the function on the given input and returns the output.

Parameters:
input - The input to evaluate.
Returns:
The output produced by evaluating the input.