Class

com.microsoft.ml.spark

RegressorTrainParams

Related Doc: package spark

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case class RegressorTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, objective: String, alpha: Double, tweedieVariancePower: Double, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, modelString: String) extends TrainParams with Product with Serializable

Defines the Booster parameters passed to the LightGBM regressor.

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  1. RegressorTrainParams
  2. Product
  3. Equals
  4. TrainParams
  5. Serializable
  6. Serializable
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Instance Constructors

  1. new RegressorTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, objective: String, alpha: Double, tweedieVariancePower: Double, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, modelString: String)

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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. val alpha: Double

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  5. final def asInstanceOf[T0]: T0

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  6. val baggingFraction: Double

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    RegressorTrainParamsTrainParams
  7. val baggingFreq: Int

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    RegressorTrainParamsTrainParams
  8. val baggingSeed: Int

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    RegressorTrainParamsTrainParams
  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )
  10. val earlyStoppingRound: Int

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    RegressorTrainParamsTrainParams
  11. final def eq(arg0: AnyRef): Boolean

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  12. val featureFraction: Double

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    RegressorTrainParamsTrainParams
  13. def finalize(): Unit

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

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  15. final def isInstanceOf[T0]: Boolean

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  16. val learningRate: Double

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    RegressorTrainParamsTrainParams
  17. val maxBin: Int

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    RegressorTrainParamsTrainParams
  18. val maxDepth: Int

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    RegressorTrainParamsTrainParams
  19. val minSumHessianInLeaf: Double

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    RegressorTrainParamsTrainParams
  20. val modelString: String

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    RegressorTrainParamsTrainParams
  21. final def ne(arg0: AnyRef): Boolean

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  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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  24. val numIterations: Int

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    RegressorTrainParamsTrainParams
  25. val numLeaves: Int

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    RegressorTrainParamsTrainParams
  26. val numMachines: Int

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    RegressorTrainParamsTrainParams
  27. val objective: String

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    RegressorTrainParamsTrainParams
  28. val parallelism: String

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

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  30. def toString(): String

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    RegressorTrainParamsTrainParams → AnyRef → Any
  31. val tweedieVariancePower: Double

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  32. final def wait(): Unit

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

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

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Inherited from Product

Inherited from Equals

Inherited from TrainParams

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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