org.dmg.pmml

Interface HasExtensions<E extends PMMLObject & HasExtensions<E>>

All Known Implementing Classes:

AbsoluteExponentialKernel, Aggregate, Alternate, Anova, AnovaRow, AntecedentSequence, AnyDistribution, Application, Apply, ARDSquaredExponentialKernel, AssociationModel, AssociationRule, Attribute, BaseCumHazardTables, Baseline, BaselineCell, BaselineModel, BaselineStratum, BayesianNetworkModel, BayesianNetworkNodes, BayesInput, BayesInputs, BayesOutput, BinarySimilarity, BoundaryValueMeans, BoundaryValues, CategoricalPredictor, Categories, Category, Characteristic, Characteristics, Chebychev, ChildParent, CityBlock, ClassLabels, Cluster, ClusteringField, ClusteringModel, Coefficient, Coefficients, ComparisonMeasure, Comparisons, ComplexNode, ComplexPartialScore, CompoundPredicate, CompoundRule, ConfusionMatrix, Connection, ConsequentSequence, Constraints, ContinuousConditionalProbability, ContinuousDistribution, ContinuousNode, ContStats, CorrelationFields, CorrelationMethods, Correlations, CorrelationValues, Counts, CountTable, Covariances, CovariateList, DataDictionary, DataField, Decision, Decisions, DecisionTree, DefineFunction, Delimiter, DerivedField, DiscreteConditionalProbability, DiscreteNode, Discretize, DiscretizeBin, DiscrStats, DocumentTermMatrix, Euclidean, EventValues, FactorList, False, FieldColumnPair, FieldRef, FieldValue, FieldValueCount, GaussianDistribution, GaussianProcessModel, GeneralizedExponentialKernel, GeneralRegressionModel, Header, InlineTable, InstanceField, InstanceFields, Interval, Item, ItemRef, Itemset, Jaccard, KNNInput, KNNInputs, KohonenMap, Lag, Lambda, LiftData, LiftGraph, LinearKernel, LinearNorm, LocalTransformations, LognormalDistribution, Lower, MapValues, Mean, MiningBuildTask, MiningField, MiningModel, MiningSchema, Minkowski, MissingValueWeights, ModelExplanation, ModelLiftGraph, ModelStats, ModelVerification, MultivariateStat, MultivariateStats, NaiveBayesModel, NearestNeighborModel, NeuralInput, NeuralInputs, NeuralLayer, NeuralNetwork, NeuralOutput, NeuralOutputs, Neuron, NormalDistribution, NormContinuous, NormDiscrete, NumericInfo, NumericPredictor, OptimumLiftGraph, Output, OutputField, PairCounts, Parameter, ParameterList, ParamMatrix, ParentValue, Partition, PartitionFieldStats, PCell, PCovCell, PCovMatrix, PMML, PoissonDistribution, PolynomialKernel, PPCell, PPMatrix, PredictiveModelQuality, Predictor, PredictorTerm, Quantile, RadialBasisKernel, RadialBasisKernel, RandomLiftGraph, Regression, RegressionModel, RegressionTable, ResultField, ROC, ROCGraph, RuleSelectionMethod, RuleSet, RuleSetModel, Scorecard, ScoreDistribution, Segment, Segmentation, Sequence, SequenceModel, SequenceReference, SetPredicate, SetReference, SigmoidKernel, SimpleMatching, SimplePredicate, SimpleRule, SimpleSetPredicate, SquaredEuclidean, SupportVector, SupportVectorMachine, SupportVectorMachineModel, SupportVectors, TableLocator, Tanimoto, Target, Targets, TargetValue, TargetValueCount, TargetValueCounts, TargetValueStat, TargetValueStats, Taxonomy, TestDistributions, TextCorpus, TextDictionary, TextDocument, TextIndex, TextIndexNormalization, TextModel, TextModelNormalization, TextModelSimiliarity, Time, TimeSeriesModel, TrainingInstances, TransformationDictionary, TreeModel, TriangularDistribution, True, UniformDistribution, UniformDistribution, UnivariateStats, Upper, Value, ValueProbability, Variance, VectorDictionary, VectorFields, VectorInstance, VerificationField, VerificationFields, XCoordinates, YCoordinates

public interface HasExtensions<E extends PMMLObject & HasExtensions<E>>

A marker interface for PMML elements that specify Extension child elements.

Method Summary

Modifier and Type	Method and Description
E	addExtensions(Extension... extensions)
List<Extension>	getExtensions()
boolean	hasExtensions()

Method Detail

hasExtensions

boolean hasExtensions()

getExtensions

List<Extension> getExtensions()

addExtensions

E addExtensions(Extension... extensions)