Class

org.apache.spark.mllib.feature

DiscretizerModel

Related Doc: package feature

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class DiscretizerModel extends VectorTransformer

Generic a discretizer model that transform data given a list of thresholds by feature.

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VectorTransformer, Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new DiscretizerModel(thresholds: Array[Array[Float]])

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    thresholds

    Thresholds defined for each feature (must be sorted). Note: checking the second sorting condition can be much more time-consuming. We omit this condition.

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. val thresholds: Array[Array[Float]]

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    Thresholds defined for each feature (must be sorted).

    Thresholds defined for each feature (must be sorted). Note: checking the second sorting condition can be much more time-consuming. We omit this condition.

  17. def toString(): String

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  18. def transform(data: Vector): Vector

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    Discretizes values in a given dataset using thresholds.

    Discretizes values in a given dataset using thresholds.

    data

    A single continuous-valued vector.

    returns

    A resulting vector with its values discretized (from 1 to n).

    Definition Classes
    DiscretizerModel → VectorTransformer

  19. def transform(data: JavaRDD[Vector]): JavaRDD[Vector]

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    Definition Classes
    VectorTransformer
    Annotations
    @Since( "1.1.0" )

  20. def transform(data: RDD[Vector]): RDD[Vector]

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    Definition Classes
    VectorTransformer
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    @Since( "1.1.0" )

  21. def transformRDD(data: RDD[Vector]): RDD[Vector]

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    Discretizes values in a given dataset using thresholds.

    Discretizes values in a given dataset using thresholds.

    data

    RDD with continuous-valued vectors.

    returns

    RDD with discretized data (from 1 to n).

  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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Inherited from VectorTransformer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

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