org.apache.mahout.math.algorithms.regression

OrdinaryLeastSquares

class OrdinaryLeastSquares[K] extends LinearRegressorFitter[K]

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  1. OrdinaryLeastSquares
  2. LinearRegressorFitter
  3. RegressorFitter
  4. SupervisedFitter
  5. Fitter
  6. AnyRef
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Instance Constructors

  1. new OrdinaryLeastSquares()

Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. var addIntercept: Boolean

    Definition Classes
    RegressorFitter
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. var calcCommonStatistics: Boolean

    Definition Classes
    LinearRegressorFitter
  9. var calcStandardErrors: Boolean

    Definition Classes
    LinearRegressorFitter
  10. def calculateCommonStatistics[M[K] <: LinearRegressorModel[K]](model: M[K], drmTarget: DrmLike[K], residuals: DrmLike[K]): M[K]

    Definition Classes
    LinearRegressorFitter
  11. def calculateStandardError[M[K] <: LinearRegressorModel[K]](X: DrmLike[K], drmTarget: DrmLike[K], drmXtXinv: Matrix, model: M[K]): M[K]

    Definition Classes
    LinearRegressorFitter
  12. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
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    @throws( ... )
  13. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  14. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  15. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  16. def fit(drmFeatures: DrmLike[K], drmTarget: DrmLike[K], hyperparameters: (Symbol, Any)*): OrdinaryLeastSquaresModel[K]

  17. def fitPredict(drmX: DrmLike[K], drmTarget: DrmLike[K], hyperparameters: (Symbol, Any)*): DrmLike[K]

    Definition Classes
    RegressorFitter
  18. def generateSummaryString[M[K] <: LinearRegressorModel[K]](model: M[K]): String

    Definition Classes
    LinearRegressorFitter
  19. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  20. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  21. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  22. var model: RegressorModel[K]

    Definition Classes
    RegressorFitter
  23. def modelPostprocessing[M[K] <: LinearRegressorModel[K]](model: M[K], X: DrmLike[K], drmTarget: DrmLike[K], drmXtXinv: Matrix): M[K]

    Definition Classes
    LinearRegressorFitter
  24. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  25. final def notify(): Unit

    Definition Classes
    AnyRef
  26. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  27. def setStandardHyperparameters(hyperparameters: Map[Symbol, Any] = Map('foo -> None)): Unit

    Definition Classes
    LinearRegressorFitter
  28. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  29. def toString(): String

    Definition Classes
    AnyRef → Any
  30. final def wait(): Unit

    Definition Classes
    AnyRef
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    @throws( ... )
  31. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  32. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from LinearRegressorFitter[K]

Inherited from RegressorFitter[K]

Inherited from SupervisedFitter[K, RegressorModel[K]]

Inherited from Fitter

Inherited from AnyRef

Inherited from Any

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