Packages

c

org.apache.spark.ml.boosting

ScaledLogCoshLoss

case class ScaledLogCoshLoss(alpha: Double) extends GBMRegressionLoss with HasScalarHessian with Product with Serializable

Source
GBMLoss.scala
Linear Supertypes
Product, Equals, HasScalarHessian, HasHessian, GBMRegressionLoss, GBMScalarLoss, GBMLoss, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ScaledLogCoshLoss
  2. Product
  3. Equals
  4. HasScalarHessian
  5. HasHessian
  6. GBMRegressionLoss
  7. GBMScalarLoss
  8. GBMLoss
  9. Serializable
  10. AnyRef
  11. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new ScaledLogCoshLoss(alpha: Double)

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. val alpha: Double
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  7. def dim: Int
    Definition Classes
    GBMScalarLoss → GBMLoss
  8. def encodeLabel(label: Double): Array[Double]
    Definition Classes
    GBMRegressionLoss → GBMLoss
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  11. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. def gradient(label: Double, prediction: Double): Double
    Definition Classes
    ScaledLogCoshLoss → GBMScalarLoss
  13. def gradient(label: Array[Double], prediction: Array[Double]): Array[Double]
    Definition Classes
    GBMScalarLoss → GBMLoss
  14. def hessian(label: Double, prediction: Double): Double
    Definition Classes
    ScaledLogCoshLoss → HasScalarHessian
  15. def hessian(label: Array[Double], prediction: Array[Double]): Array[Double]
    Definition Classes
    HasScalarHessian → HasHessian
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. def loss(label: Double, prediction: Double): Double
    Definition Classes
    ScaledLogCoshLoss → GBMScalarLoss
  18. def loss(label: Array[Double], prediction: Array[Double]): Double
    Definition Classes
    GBMScalarLoss → GBMLoss
  19. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. def negativeGradient(label: Double, prediction: Double): Double
    Definition Classes
    GBMScalarLoss
  21. def negativeGradient(label: Array[Double], prediction: Array[Double]): Array[Double]
    Definition Classes
    GBMLoss
  22. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. def productElementNames: Iterator[String]
    Definition Classes
    Product
  25. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  26. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  27. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  28. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()

Inherited from Product

Inherited from Equals

Inherited from HasScalarHessian

Inherited from HasHessian

Inherited from GBMRegressionLoss

Inherited from GBMScalarLoss

Inherited from GBMLoss

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped