Class/Object

ml.combust.mleap.core.regression.GeneralizedLinearRegressionModel

Family

Related Docs: object Family | package GeneralizedLinearRegressionModel

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abstract class Family extends Serializable

A description of the error distribution to be used in the model.

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Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new Family(name: String)

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    name

    the name of the family.

Abstract Value Members

  1. abstract val defaultLink: Link

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    The default link instance of this family.

  2. abstract def deviance(y: Double, mu: Double, weight: Double): Double

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    Deviance of (y, mu) pair.

  3. abstract def initialize(y: Double, weight: Double): Double

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    Initialize the starting value for mu.

  4. abstract def variance(mu: Double): Double

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    The variance of the endogenous variable's mean, given the value mu.

Concrete 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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. val name: String

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    the name of the family.

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

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    Definition Classes
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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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  16. def project(mu: Double): Double

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    Trim the fitted value so that it will be in valid range.

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

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  18. def toString(): String

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  19. final def wait(): Unit

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

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

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Inherited from Serializable

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