Class/Object

ml.combust.mleap.core.feature

HashingTermFrequencyModel

Related Docs: object HashingTermFrequencyModel | package feature

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case class HashingTermFrequencyModel(numFeatures: Int = 1 << 18, binary: Boolean = false) extends Product with Serializable

Class for hashing token frequencies into a vector.

Source adapted from: Apache Spark Utils and HashingTF, see NOTICE for contributors

numFeatures

size of feature vector to hash into

Annotations
@SparkCode()
Linear Supertypes
Serializable, Serializable, Product, Equals, AnyRef, Any
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  1. HashingTermFrequencyModel
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Instance Constructors

  1. new HashingTermFrequencyModel(numFeatures: Int = 1 << 18, binary: Boolean = false)

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    numFeatures

    size of feature vector to hash into

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. def apply(document: Iterable[_]): Vector

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  5. final def asInstanceOf[T0]: T0

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    Any
  6. val binary: Boolean

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  7. def clone(): AnyRef

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

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    AnyRef
  9. def finalize(): Unit

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

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  11. def indexOf(term: Any): Int

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  12. final def isInstanceOf[T0]: Boolean

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

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    Definition Classes
    AnyRef
  14. def nonNegativeMod(x: Int, mod: Int): Int

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    Annotations
    @SparkCode()
  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 numFeatures: Int

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    size of feature vector to hash into

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

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    Definition Classes
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  19. final def wait(): Unit

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

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

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