Package sklearn2pmml

Interface HasPMMLOptions<E extends Step>

All Known Implementing Classes:

AdaBoostRegressor, BaggingClassifier, BaggingRegressor, CalibratedClassifier, CalibratedClassifierCV, Calibrator, CHAIDClassifier, CHAIDRegressor, Classifier, ClassifierChain, Clusterer, CompositeClassifier, CompositeClusterer, CompositeRegressor, DummyClassifier, DummyRegressor, EnsembleClassifier, EnsembleRegressor, Estimator, EstimatorChain, EstimatorProxy, ExpressionClassifier, ExpressionRegressor, FixedThresholdClassifier, ForestClassifier, ForestRegressor, GaussianNB, GBDTLMRegressor, GBDTLRClassifier, GeneralizedLinearRegressor, GradientBoostingClassifier, GradientBoostingRegressor, HistGradientBoostingClassifier, HistGradientBoostingRegressor, IsolationForest, IsotonicRegression, KMeans, KNeighborsClassifier, KNeighborsRegressor, LabelEncoderClassifier, LibSVMClassifier, LibSVMRegressor, LinearClassifier, LinearDiscriminantAnalysis, LinearRegressor, LinearSVC, Link, LogisticRegression, MiniBatchKMeans, MLPClassifier, MLPRegressor, MultiOutputClassifier, MultiOutputRegressor, NearestCentroid, NearestNeighbors, OneClassSVM, OneVsRestClassifier, PMMLPipeline, Regressor, RegressorChain, RidgeClassifier, RuleSetClassifier, SelectFirstClassifier, SelectFirstRegressor, SGDClassifier, SGDOneClassSVM, SigmoidCalibration, SkLearnClassifier, SkLearnClusterer, SkLearnRegressor, StackingClassifier, StackingRegressor, TransformedTargetRegressor, TreeClassifier, TreeRegressor, TunedThresholdClassifierCV, VotingClassifier, VotingRegressor

public interface HasPMMLOptions<E extends Step>

See Also:

SkLearn2PMMLFields.PMML_OPTIONS

Method Summary

Modifier and Type	Method	Description
java.util.Map<java.lang.String,?>	getPMMLOptions()
E	setPMMLOptions(java.util.Map<java.lang.String,?> pmmlOptions)

Method Detail

getPMMLOptions

java.util.Map<java.lang.String,?> getPMMLOptions()

setPMMLOptions

E setPMMLOptions(java.util.Map<java.lang.String,?> pmmlOptions)