Trait

org.apache.spark.ml.util

MLReadable

Related Doc: package util

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trait MLReadable[T] extends AnyRef

Trait for objects that provide MLReader.

T

ML instance type

Annotations
@Since( "1.6.0" )
Source
ReadWrite.scala
Linear Supertypes
AnyRef, Any
Known Subclasses
AFTSurvivalRegression, AFTSurvivalRegressionModel, ALS, ALSModel, Binarizer, BinaryClassificationEvaluator, BisectingKMeans, BisectingKMeansModel, BucketedRandomProjectionLSH, BucketedRandomProjectionLSHModel, Bucketizer, ChiSqSelector, ChiSqSelectorModel, CountVectorizer, CountVectorizerModel, CrossValidator, CrossValidatorModel, DCT, DecisionTreeClassificationModel, DecisionTreeClassifier, DecisionTreeRegressionModel, DecisionTreeRegressor, DefaultParamsReadable, DistributedLDAModel, ElementwiseProduct, GBTClassificationModel, GBTClassifier, GBTRegressionModel, GBTRegressor, GaussianMixture, GaussianMixtureModel, GeneralizedLinearRegression, GeneralizedLinearRegressionModel, HashingTF, IDF, IDFModel, IndexToString, Interaction, IsotonicRegression, IsotonicRegressionModel, KMeans, KMeansModel, LDA, LinearRegression, LinearRegressionModel, LocalLDAModel, LogisticRegression, LogisticRegressionModel, MaxAbsScaler, MaxAbsScalerModel, MinHashLSH, MinHashLSHModel, MinMaxScaler, MinMaxScalerModel, MulticlassClassificationEvaluator, MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier, NGram, NaiveBayes, NaiveBayesModel, Normalizer, OneHotEncoder, OneVsRest, OneVsRestModel, PCA, PCAModel, Pipeline, PipelineModel, PolynomialExpansion, QuantileDiscretizer, RFormula, RFormulaModel, RandomForestClassificationModel, RandomForestClassifier, RandomForestRegressionModel, RandomForestRegressor, RegexTokenizer, RegressionEvaluator, SQLTransformer, StandardScaler, StandardScalerModel, StopWordsRemover, StringIndexer, StringIndexerModel, Tokenizer, TrainValidationSplit, TrainValidationSplitModel, VectorAssembler, VectorIndexer, VectorIndexerModel, VectorSlicer, Word2Vec, Word2VecModel
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Inherited
  1. MLReadable
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Visibility
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Abstract Value Members

  1. abstract def read: MLReader[T]

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    Returns an MLReader instance for this class.

    Returns an MLReader instance for this class.

    Annotations
    @Since( "1.6.0" )

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. def load(path: String): T

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    Reads an ML instance from the input path, a shortcut of read.load(path).

    Reads an ML instance from the input path, a shortcut of read.load(path).

    Annotations
    @Since( "1.6.0" )
    Note

    Implementing classes should override this to be Java-friendly.

  13. final def ne(arg0: AnyRef): Boolean

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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  16. final def synchronized[T0](arg0: ⇒ T0): T0

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  17. def toString(): String

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  18. final def wait(): Unit

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    @throws( ... )
  19. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  20. final def wait(arg0: Long): Unit

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Inherited from AnyRef

Inherited from Any

Members