c

com.microsoft.azure.synapse.ml.lightgbm.params

ClassifierTrainParams

case class ClassifierTrainParams(parallelism: String, topK: Option[Int], numIterations: Int, learningRate: Double, numLeaves: Option[Int], maxBin: Option[Int], binSampleCount: Option[Int], baggingFraction: Option[Double], posBaggingFraction: Option[Double], negBaggingFraction: Option[Double], baggingFreq: Option[Int], baggingSeed: Option[Int], earlyStoppingRound: Int, improvementTolerance: Double, featureFraction: Option[Double], maxDepth: Option[Int], minSumHessianInLeaf: Option[Double], numMachines: Int, modelString: Option[String], isUnbalance: Boolean, verbosity: Int, categoricalFeatures: Array[Int], numClass: Int, boostFromAverage: Boolean, boostingType: String, lambdaL1: Option[Double], lambdaL2: Option[Double], isProvideTrainingMetric: Option[Boolean], metric: Option[String], minGainToSplit: Option[Double], maxDeltaStep: Option[Double], maxBinByFeature: Array[Int], minDataInLeaf: Option[Int], featureNames: Array[String], delegate: Option[LightGBMDelegate], dartModeParams: DartModeParams, executionParams: ExecutionParams, objectiveParams: ObjectiveParams) extends TrainParams with Product with Serializable

Defines the Booster parameters passed to the LightGBM classifier.

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

  1. new ClassifierTrainParams(parallelism: String, topK: Option[Int], numIterations: Int, learningRate: Double, numLeaves: Option[Int], maxBin: Option[Int], binSampleCount: Option[Int], baggingFraction: Option[Double], posBaggingFraction: Option[Double], negBaggingFraction: Option[Double], baggingFreq: Option[Int], baggingSeed: Option[Int], earlyStoppingRound: Int, improvementTolerance: Double, featureFraction: Option[Double], maxDepth: Option[Int], minSumHessianInLeaf: Option[Double], numMachines: Int, modelString: Option[String], isUnbalance: Boolean, verbosity: Int, categoricalFeatures: Array[Int], numClass: Int, boostFromAverage: Boolean, boostingType: String, lambdaL1: Option[Double], lambdaL2: Option[Double], isProvideTrainingMetric: Option[Boolean], metric: Option[String], minGainToSplit: Option[Double], maxDeltaStep: Option[Double], maxBinByFeature: Array[Int], minDataInLeaf: Option[Int], featureNames: Array[String], delegate: Option[LightGBMDelegate], dartModeParams: DartModeParams, executionParams: ExecutionParams, objectiveParams: ObjectiveParams)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. val baggingFraction: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  6. val baggingFreq: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  7. val baggingSeed: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  8. val binSampleCount: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  9. val boostFromAverage: Boolean
  10. val boostingType: String
    Definition Classes
    ClassifierTrainParamsTrainParams
  11. val categoricalFeatures: Array[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  12. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  13. val dartModeParams: DartModeParams
    Definition Classes
    ClassifierTrainParamsTrainParams
  14. val delegate: Option[LightGBMDelegate]
    Definition Classes
    ClassifierTrainParamsTrainParams
  15. val earlyStoppingRound: Int
    Definition Classes
    ClassifierTrainParamsTrainParams
  16. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. val executionParams: ExecutionParams
    Definition Classes
    ClassifierTrainParamsTrainParams
  18. val featureFraction: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  19. val featureNames: Array[String]
    Definition Classes
    ClassifierTrainParamsTrainParams
  20. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  22. val improvementTolerance: Double
    Definition Classes
    ClassifierTrainParamsTrainParams
  23. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  24. val isProvideTrainingMetric: Option[Boolean]
    Definition Classes
    ClassifierTrainParamsTrainParams
  25. val isUnbalance: Boolean
  26. val lambdaL1: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  27. val lambdaL2: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  28. val learningRate: Double
    Definition Classes
    ClassifierTrainParamsTrainParams
  29. val maxBin: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  30. val maxBinByFeature: Array[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  31. val maxDeltaStep: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  32. val maxDepth: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  33. val metric: Option[String]
    Definition Classes
    ClassifierTrainParamsTrainParams
  34. val minDataInLeaf: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  35. val minGainToSplit: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  36. val minSumHessianInLeaf: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  37. val modelString: Option[String]
    Definition Classes
    ClassifierTrainParamsTrainParams
  38. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  39. val negBaggingFraction: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  40. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  41. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  42. val numClass: Int
  43. val numIterations: Int
    Definition Classes
    ClassifierTrainParamsTrainParams
  44. val numLeaves: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  45. val numMachines: Int
    Definition Classes
    ClassifierTrainParamsTrainParams
  46. val objectiveParams: ObjectiveParams
    Definition Classes
    ClassifierTrainParamsTrainParams
  47. val parallelism: String
    Definition Classes
    ClassifierTrainParamsTrainParams
  48. def paramToString[T](paramName: String, paramValueOpt: Option[T]): String
    Definition Classes
    TrainParams
  49. def paramsToString(paramNamesToValues: Array[(String, Option[_])]): String
    Definition Classes
    TrainParams
  50. val posBaggingFraction: Option[Double]
    Definition Classes
    ClassifierTrainParamsTrainParams
  51. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  52. def toString(): String
    Definition Classes
    ClassifierTrainParamsTrainParams → AnyRef → Any
  53. val topK: Option[Int]
    Definition Classes
    ClassifierTrainParamsTrainParams
  54. val verbosity: Int
    Definition Classes
    ClassifierTrainParamsTrainParams
  55. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  57. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Product

Inherited from Equals

Inherited from TrainParams

Inherited from Serializable

Inherited from Serializable

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