PipelineRegressionTransformer

Value Members

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

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

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

   

   Definition Classes

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4. def allowNullValues: Boolean

   

   Allows the transformer to specify if the apply method can handle null values in the input row.

   Allows the transformer to specify if the apply method can handle null values in the input row.

   e.g. a Null value replacement transformer, or a Naive Bayes transformer would naturally handle null values, but a Linear Regression transformer would not.

   Default value is false.

   returns

   Boolean indicating tolerance for null values in input.

   Definition Classes

   Transformer

5. def apply(row: Row): Row

   

   This method should be implemented with speed and garbage collection in mind, as it called once per row on potentially huge data-sets.

   This method should be implemented with speed and garbage collection in mind, as it called once per row on potentially huge data-sets.

   This method is not required to be thread-safe.

   row

   The row of input to be scored.

   returns

   The result from applying the trained model to the row.

   Definition Classes

   PipelineRegressionTransformer → RegressionTransformer → PipelineTransformer → Transformer

6. def apply(row: Row, tList: List[Transformer], reordering: List[Option[Array[Int]]]): Row

   

   Attributes

   protected

   Definition Classes

   PipelineTransformer

7. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

8. def clone(): AnyRef

   

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   protected[java.lang]

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   @throws( ... )

9. final def eq(arg0: AnyRef): Boolean

   

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   AnyRef

10. def equals(arg0: Any): Boolean

    

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11. def finalize(): Unit

    

    Attributes

    protected[java.lang]

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    @throws( classOf[java.lang.Throwable] )

12. final def getClass(): Class[_]

    

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13. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

14. def inputRowForLastModel(row: Row): Row

    

    Attributes

    protected

    Definition Classes

    PipelineMLTransformer

15. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

16. val lastReordering: Option[Array[Int]]

    

    Attributes

    protected

    Definition Classes

    PipelineTransformer

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

    

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18. final def notify(): Unit

    

    Definition Classes

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19. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

20. def predict(row: Row): Double

    

    Definition Classes

    PipelineRegressionTransformer → RegressionTransformer

21. val reorderingIndices: List[Option[Array[Int]]]

    

    Attributes

    protected

    Definition Classes

    PipelineTransformer

22. def score(row: Row): RealResult

    

    Definition Classes

    PipelineRegressionTransformer → RegressionTransformer → PipelineMLTransformer → MLTransformer

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

    

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24. def toString(): String

    

    Definition Classes

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25. final def wait(): Unit

    

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    @throws( ... )

26. final def wait(arg0: Long, arg1: Int): Unit

    

    Definition Classes

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    @throws( ... )

27. final def wait(arg0: Long): Unit

    

    Definition Classes

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    @throws( ... )