org.apache.spark.ml.util

Interface Identifiable

All Known Subinterfaces:

AFTSurvivalRegressionParams, ALSModelParams, ALSParams, BisectingKMeansParams, BucketedRandomProjectionLSHParams, ClassifierParams, CountVectorizerParams, CrossValidatorParams, DecisionTreeClassifierParams, DecisionTreeParams, DecisionTreeRegressorParams, FactorizationMachines, FactorizationMachinesParams, FMClassifierParams, FMRegressorParams, FPGrowthParams, GaussianMixtureParams, GBTClassifierParams, GBTParams, GBTRegressorParams, GeneralizedLinearRegressionBase, HasAggregationDepth, HasBlockSize, HasCheckpointInterval, HasCollectSubModels, HasDistanceMeasure, HasElasticNetParam, HasFeaturesCol, HasFitIntercept, HasHandleInvalid, HasInputCol, HasInputCols, HasLabelCol, HasLoss, HasMaxBlockSizeInMB, HasMaxIter, HasNumFeatures, HasOutputCol, HasOutputCols, HasParallelism, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, HasRegParam, HasRelativeError, HasSeed, HasSolver, HasStandardization, HasStepSize, HasThreshold, HasThresholds, HasTol, HasValidationIndicatorCol, HasVarianceCol, HasVarianceImpurity, HasWeightCol, IDFBase, ImputerParams, IsotonicRegressionBase, KMeansParams, LDAParams, LinearRegressionParams, LinearSVCParams, LogisticRegressionParams, LSHParams, MaxAbsScalerParams, MinMaxScalerParams, MultilayerPerceptronParams, NaiveBayesParams, OneHotEncoderBase, OneVsRestParams, Params, PCAParams, PowerIterationClusteringParams, PredictorParams, ProbabilisticClassifierParams, QuantileDiscretizerBase, RandomForestClassifierParams, RandomForestParams, RandomForestRegressorParams, RFormulaBase, RobustScalerParams, SelectorParams, StandardScalerParams, StringIndexerBase, TrainValidationSplitParams, TreeClassifierParams, TreeEnsembleClassifierParams, TreeEnsembleParams, TreeEnsembleRegressorParams, TreeRegressorParams, UnivariateFeatureSelectorParams, ValidatorParams, VarianceThresholdSelectorParams, VectorIndexerParams, Word2VecBase

All Known Implementing Classes:

AFTSurvivalRegression, AFTSurvivalRegressionModel, ALS, ALSModel, Binarizer, BinaryClassificationEvaluator, BisectingKMeans, BisectingKMeansModel, BucketedRandomProjectionLSH, BucketedRandomProjectionLSHModel, Bucketizer, ChiSqSelector, ChiSqSelectorModel, ClassificationModel, Classifier, ClusteringEvaluator, ColumnPruner, CountVectorizer, CountVectorizerModel, CrossValidator, CrossValidatorModel, DCT, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeRegressionModel, DecisionTreeRegressor, DistributedLDAModel, ElementwiseProduct, Estimator, Evaluator, FeatureHasher, FMClassificationModel, FMClassifier, FMRegressionModel, FMRegressor, FPGrowth, FPGrowthModel, GaussianMixture, GaussianMixtureModel, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GeneralizedLinearRegression, GeneralizedLinearRegressionModel, HashingTF, IDF, IDFModel, Imputer, ImputerModel, IndexToString, Interaction, IsotonicRegression, IsotonicRegressionModel, JavaParams, KMeans, KMeansModel, LDA, LDAModel, LinearRegression, LinearRegressionModel, LinearSVC, LinearSVCModel, LocalLDAModel, LogisticRegression, LogisticRegressionModel, MaxAbsScaler, MaxAbsScalerModel, MinHashLSH, MinHashLSHModel, MinMaxScaler, MinMaxScalerModel, Model, MulticlassClassificationEvaluator, MultilabelClassificationEvaluator, MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier, NaiveBayes, NaiveBayesModel, NGram, Normalizer, OneHotEncoder, OneHotEncoderModel, OneVsRest, OneVsRestModel, PCA, PCAModel, Pipeline, PipelineModel, PipelineStage, PolynomialExpansion, PowerIterationClustering, PredictionModel, Predictor, PrefixSpan, ProbabilisticClassificationModel, ProbabilisticClassifier, QuantileDiscretizer, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RankingEvaluator, RegexTokenizer, RegressionEvaluator, RegressionModel, Regressor, RFormula, RFormulaModel, RobustScaler, RobustScalerModel, SQLTransformer, StandardScaler, StandardScalerModel, StopWordsRemover, StringIndexer, StringIndexerModel, Tokenizer, TrainValidationSplit, TrainValidationSplitModel, Transformer, UnaryTransformer, UnivariateFeatureSelector, UnivariateFeatureSelectorModel, VarianceThresholdSelector, VarianceThresholdSelectorModel, VectorAssembler, VectorAttributeRewriter, VectorIndexer, VectorIndexerModel, VectorSizeHint, VectorSlicer, Word2Vec, Word2VecModel

public interface Identifiable

Trait for an object with an immutable unique ID that identifies itself and its derivatives.

WARNING: There have not yet been final discussions on this API, so it may be broken in future releases.

Method Summary

Modifier and Type	Method and Description
String	toString()
String	uid() An immutable unique ID for the object and its derivatives.

Method Detail

uid

String uid()

An immutable unique ID for the object and its derivatives.

Returns:

(undocumented)

toString

String toString()

Overrides:

toString in class Object