Class

com.microsoft.ml.spark.lightgbm

RankerTrainParams

Related Doc: package lightgbm

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case class RankerTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, objective: String, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, modelString: Option[String], verbosity: Int, categoricalFeatures: Array[Int], boostingType: String, lambdaL1: Double, lambdaL2: Double, maxPosition: Int, labelGain: Array[Double], isProvideTrainingMetric: Boolean, metric: String, evalAt: Array[Int]) extends TrainParams with Product with Serializable

Defines the Booster parameters passed to the LightGBM ranker.

Linear Supertypes
Product, Equals, TrainParams, Serializable, Serializable, AnyRef, Any
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Inherited
  1. RankerTrainParams
  2. Product
  3. Equals
  4. TrainParams
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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Visibility
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Instance Constructors

  1. new RankerTrainParams(parallelism: String, numIterations: Int, learningRate: Double, numLeaves: Int, objective: String, maxBin: Int, baggingFraction: Double, baggingFreq: Int, baggingSeed: Int, earlyStoppingRound: Int, featureFraction: Double, maxDepth: Int, minSumHessianInLeaf: Double, numMachines: Int, modelString: Option[String], verbosity: Int, categoricalFeatures: Array[Int], boostingType: String, lambdaL1: Double, lambdaL2: Double, maxPosition: Int, labelGain: Array[Double], isProvideTrainingMetric: Boolean, metric: String, evalAt: Array[Int])

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Value Members

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

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    Definition Classes
    AnyRef → Any

  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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    Any

  5. val baggingFraction: Double

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    Definition Classes
    RankerTrainParams → TrainParams

  6. val baggingFreq: Int

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    Definition Classes
    RankerTrainParams → TrainParams

  7. val baggingSeed: Int

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    Definition Classes
    RankerTrainParams → TrainParams

  8. val boostingType: String

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    Definition Classes
    RankerTrainParams → TrainParams

  9. val categoricalFeatures: Array[Int]

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    Definition Classes
    RankerTrainParams → TrainParams

  10. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  11. val earlyStoppingRound: Int

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    Definition Classes
    RankerTrainParams → TrainParams

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

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    AnyRef

  13. val evalAt: Array[Int]

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  14. val featureFraction: Double

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    Definition Classes
    RankerTrainParams → TrainParams

  15. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    AnyRef → Any

  17. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  18. val isProvideTrainingMetric: Boolean

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    Definition Classes
    RankerTrainParams → TrainParams

  19. val labelGain: Array[Double]

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  20. val lambdaL1: Double

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    Definition Classes
    RankerTrainParams → TrainParams

  21. val lambdaL2: Double

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    RankerTrainParams → TrainParams

  22. val learningRate: Double

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    RankerTrainParams → TrainParams

  23. val maxBin: Int

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    RankerTrainParams → TrainParams

  24. val maxDepth: Int

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    Definition Classes
    RankerTrainParams → TrainParams

  25. val maxPosition: Int

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  26. val metric: String

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    Definition Classes
    RankerTrainParams → TrainParams

  27. val minSumHessianInLeaf: Double

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    Definition Classes
    RankerTrainParams → TrainParams

  28. val modelString: Option[String]

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    RankerTrainParams → TrainParams

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

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    AnyRef

  30. final def notify(): Unit

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  31. final def notifyAll(): Unit

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  32. val numIterations: Int

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    RankerTrainParams → TrainParams

  33. val numLeaves: Int

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    RankerTrainParams → TrainParams

  34. val numMachines: Int

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    RankerTrainParams → TrainParams

  35. val objective: String

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    Definition Classes
    RankerTrainParams → TrainParams

  36. val parallelism: String

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    Definition Classes
    RankerTrainParams → TrainParams

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

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    Definition Classes
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  38. def toString(): String

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    RankerTrainParams → TrainParams → AnyRef → Any

  39. val verbosity: Int

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    RankerTrainParams → TrainParams

  40. final def wait(): Unit

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    Annotations
    @throws( ... )

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

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    @throws( ... )

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

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    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from TrainParams

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped