Class/Object

org.apache.flink.ml.pipeline

ChainedTransformer

Related Docs: object ChainedTransformer | package pipeline

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case class ChainedTransformer[L <: Transformer[L], R <: Transformer[R]](left: L, right: R) extends Transformer[ChainedTransformer[L, R]] with Product with Serializable

Transformer which represents the chaining of two Transformer.

A ChainedTransformer can be treated as regular Transformer. Upon calling the fit or transform operation, the data is piped through all Transformer of the pipeline.

The pipeline mechanism has been inspired by scikit-learn

L

Type of the left Transformer

R

Type of the right Transformer

left

Left Transformer of the pipeline

right

Right Transformer of the pipeline

Linear Supertypes
Product, Equals, Transformer[ChainedTransformer[L, R]], Serializable, Serializable, Estimator[ChainedTransformer[L, R]], WithParameters, AnyRef, Any
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Inherited
  1. ChainedTransformer
  2. Product
  3. Equals
  4. Transformer
  5. Serializable
  6. Serializable
  7. Estimator
  8. WithParameters
  9. AnyRef
  10. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ChainedTransformer(left: L, right: R)

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    left

    Left Transformer of the pipeline

    right

    Right Transformer of the pipeline

Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  5. def chainPredictor[P <: Predictor[P]](predictor: P): ChainedPredictor[ChainedTransformer[L, R], P]

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    Chains a Transformer with a Predictor to form a ChainedPredictor.

    Chains a Transformer with a Predictor to form a ChainedPredictor.

    P

    Type of the Predictor

    predictor

    Trailing Predictor of the resulting pipeline

    Definition Classes
    Transformer
  6. def chainTransformer[T <: Transformer[T]](transformer: T): ChainedTransformer[ChainedTransformer[L, R], T]

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    Chains two Transformer to form a ChainedTransformer.

    Chains two Transformer to form a ChainedTransformer.

    T

    Type of the Transformer

    transformer

    Right side transformer of the resulting pipeline

    Definition Classes
    Transformer
  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  9. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. def fit[Training](training: DataSet[Training], fitParameters: ParameterMap = ParameterMap.Empty)(implicit fitOperation: FitOperation[ChainedTransformer[L, R], Training]): Unit

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    Fits the estimator to the given input data.

    Fits the estimator to the given input data. The fitting logic is contained in the FitOperation. The computed state will be stored in the implementing class.

    Training

    Type of the training data

    training

    Training data

    fitParameters

    Additional parameters for the FitOperation

    fitOperation

    FitOperation which encapsulates the algorithm logic

    Definition Classes
    Estimator
  11. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  12. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  13. val left: L

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    Left Transformer of the pipeline

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

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    Definition Classes
    AnyRef
  15. final def notify(): Unit

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    Definition Classes
    AnyRef
  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  17. val parameters: ParameterMap

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    Definition Classes
    WithParameters
  18. val right: R

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    Right Transformer of the pipeline

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

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    Definition Classes
    AnyRef
  20. def transform[Input, Output](input: DataSet[Input], transformParameters: ParameterMap = ParameterMap.Empty)(implicit transformOperation: TransformDataSetOperation[ChainedTransformer[L, R], Input, Output]): DataSet[Output]

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    Transform operation which transforms an input DataSet of type I into an output DataSet of type O.

    Transform operation which transforms an input DataSet of type I into an output DataSet of type O. The actual transform operation is implemented within the TransformDataSetOperation.

    Input

    Input data type

    Output

    Output data type

    input

    Input DataSet of type I

    transformParameters

    Additional parameters for the TransformDataSetOperation

    transformOperation

    TransformDataSetOperation which encapsulates the algorithm's logic

    Definition Classes
    Transformer
  21. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from Transformer[ChainedTransformer[L, R]]

Inherited from Serializable

Inherited from Serializable

Inherited from Estimator[ChainedTransformer[L, R]]

Inherited from WithParameters

Inherited from AnyRef

Inherited from Any

Ungrouped