Package org.apache.spark.ml.util
Interface Identifiable
- All Known Subinterfaces:
HasAggregationDepth,HasBlockSize,HasCheckpointInterval,HasCollectSubModels,HasDistanceMeasure,HasElasticNetParam,HasFeaturesCol,HasFitIntercept,HasHandleInvalid,HasInputCol,HasInputCols,HasLabelCol,HasLoss,HasMaxBlockSizeInMB,HasMaxIter,HasNumFeatures,HasOutputCol,HasOutputCols,HasPredictionCol,HasProbabilityCol,HasRawPredictionCol,HasRegParam,HasRelativeError,HasSeed,HasSolver,HasStandardization,HasStepSize,HasThreshold,HasThresholds,HasTol,HasValidationIndicatorCol,HasVarianceCol,HasWeightCol,Params
- All Known Implementing Classes:
AFTSurvivalRegression,AFTSurvivalRegressionModel,ALS,ALSModel,Binarizer,BinaryClassificationEvaluator,BisectingKMeans,BisectingKMeansModel,BucketedRandomProjectionLSH,BucketedRandomProjectionLSHModel,Bucketizer,ChiSqSelector,ChiSqSelectorModel,ClassificationModel,Classifier,ClusteringEvaluator,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,org.apache.spark.ml.feature.LSH,org.apache.spark.ml.feature.LSHModel,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,org.apache.spark.ml.feature.Selector,org.apache.spark.ml.feature.SelectorModel,SQLTransformer,StandardScaler,StandardScalerModel,StopWordsRemover,StringIndexer,StringIndexerModel,TargetEncoder,TargetEncoderModel,Tokenizer,TrainValidationSplit,TrainValidationSplitModel,Transformer,UnaryTransformer,UnivariateFeatureSelector,UnivariateFeatureSelectorModel,VarianceThresholdSelector,VarianceThresholdSelectorModel,VectorAssembler,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.
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Method Summary