ml.combust.mleap.core.feature

MinMaxScalerModel

case class MinMaxScalerModel(originalMin: Vector, originalMax: Vector) extends Serializable with Product

Class for MinMax Scaler Transformer

MinMax Scaler will use the Min/Max values to scale input features.

originalMin

minimum values from training features

originalMax

maximum values from training features

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Instance Constructors

  1. new MinMaxScalerModel(originalMin: Vector, originalMax: Vector)

    originalMin

    minimum values from training features

    originalMax

    maximum values from training features

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. def apply(vector: Vector): Vector

    Scale a feature vector using the min/max

    Scale a feature vector using the min/max

    vector

    feature vector

    returns

    scaled feature fector

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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

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  10. def finalize(): Unit

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

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  12. final def isInstanceOf[T0]: Boolean

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  13. val minArray: Array[Double]

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. val originalMax: Vector

    maximum values from training features

  18. val originalMin: Vector

    minimum values from training features

  19. val originalRange: Array[Double]

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

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  21. final def wait(): Unit

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

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

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