Encodable (JPMML SkLearn converter 1.9.9 API)

All Known Implementing Classes:

AdaBoostRegressor, BaggingClassifier, BaggingRegressor, BaseEncoder, BasePCA, Binarizer, CalibratedClassifier, CalibratedClassifierCV, Calibrator, ClassifierChain, ColumnTransformer, CountVectorizer, DummyClassifier, DummyRegressor, EnsembleClassifier, EnsembleRegressor, FeatureUnion, FixedThresholdClassifier, ForestClassifier, ForestRegressor, FunctionTransformer, GaussianNB, GeneralizedLinearRegressor, GradientBoostingClassifier, GradientBoostingRegressor, HistGradientBoostingClassifier, HistGradientBoostingRegressor, Imputer, IncrementalPCA, IsolationForest, IsotonicRegression, KBinsDiscretizer, KMeans, KNeighborsClassifier, KNeighborsRegressor, LabelBinarizer, LabelEncoder, LibSVMClassifier, LibSVMRegressor, LinearClassifier, LinearDiscriminantAnalysis, LinearRegressor, LinearSVC, LogisticRegression, MaxAbsScaler, MiniBatchKMeans, MinMaxScaler, MissingIndicator, MLPClassifier, MLPRegressor, MultiOneHotEncoder, MultiOutputClassifier, MultiOutputRegressor, NearestCentroid, NearestNeighbors, OneClassSVM, OneHotEncoder, OneVsRestClassifier, OrdinalEncoder, PCA, PMMLLabelBinarizer, PMMLLabelEncoder, PMMLPipeline, PolynomialFeatures, PowerTransformer, RegressorChain, RidgeClassifier, RobustScaler, Scaler, SGDClassifier, SGDOneClassSVM, SigmoidCalibration, SimpleImputer, SkLearnClassifier, SkLearnClusterer, SkLearnPipeline, SkLearnRegressor, SkLearnTransformer, SplineTransformer, StackingClassifier, StackingRegressor, StandardScaler, TargetEncoder, TfidfVectorizer, TransformedTargetRegressor, TreeClassifier, TreeRegressor, TruncatedSVD, TunedThresholdClassifierCV, VotingClassifier, VotingRegressor
```
public interface Encodable
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- Method Summary
  
  All Methods Instance Methods Abstract Methods
  Modifier and Type Method Description
  
  org.dmg.pmml.PMML encodePMML()

- Method Detail
  - encodePMML
```
org.dmg.pmml.PMML encodePMML()
```