WordFrequencyEncoder

Value Members

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

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

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3. final def ##(): Int

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4. final def ==(arg0: AnyRef): Boolean

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

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6. final def asInstanceOf[T0]: T0

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7. def clone(): AnyRef

   Attributes

   protected[java.lang]

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   @throws( ... )

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

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9. def equals(arg0: Any): Boolean

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10. def execute(deps: Seq[Expression]): TransformerExpression

    Definition Classes

    EstimatorOperator → Operator

11. def finalize(): Unit

    Attributes

    protected[java.lang]

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    Annotations

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

12. def fit(data: RDD[Seq[String]]): WordFrequencyTransformer

    The type-safe method that ML developers need to implement when writing new Estimators.

    The type-safe method that ML developers need to implement when writing new Estimators.

    data

    The estimator's training data.

    returns

    A new transformer

    Definition Classes

    WordFrequencyEncoder → Estimator

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

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    AnyRef → Any

14. def hashCode(): Int

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15. final def isInstanceOf[T0]: Boolean

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16. def label: String

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    Operator

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

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18. final def notify(): Unit

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19. final def notifyAll(): Unit

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

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21. def toString(): String

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    AnyRef → Any

22. final def wait(): Unit

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    @throws( ... )

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

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

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    @throws( ... )

25. final def withData(data: PipelineDataset[Seq[String]]): Pipeline[Seq[String], Seq[Int]]

    Constructs a pipeline that fits this estimator to training data, then applies the resultant transformer to the Pipeline input.

    Constructs a pipeline that fits this estimator to training data, then applies the resultant transformer to the Pipeline input.

    data

    The training data

    returns

    A pipeline that fits this estimator and applies the result to inputs.

    Definition Classes

    Estimator

26. final def withData(data: RDD[Seq[String]]): Pipeline[Seq[String], Seq[Int]]

    Constructs a pipeline that fits this estimator to training data, then applies the resultant transformer to the Pipeline input.

    Constructs a pipeline that fits this estimator to training data, then applies the resultant transformer to the Pipeline input.

    data

    The training data

    returns

    A pipeline that fits this estimator and applies the result to inputs.

    Definition Classes

    Estimator