org.apache.mahout.math.algorithms.regression

LinearRegressorFitter

trait LinearRegressorFitter[K] extends RegressorFitter[K]

Linear Supertypes
RegressorFitter[K], SupervisedFitter[K, RegressorModel[K]], Fitter, AnyRef, Any
Known Subclasses
CochraneOrcutt, OrdinaryLeastSquares
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. LinearRegressorFitter
  2. RegressorFitter
  3. SupervisedFitter
  4. Fitter
  5. AnyRef
  6. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract def fit(drmX: DrmLike[K], drmTarget: DrmLike[K], hyperparameters: (Symbol, Any)*): LinearRegressorModel[K]

    Definition Classes
    LinearRegressorFitter → SupervisedFitter

Concrete 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

  9. var calcStandardErrors: Boolean

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

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

  12. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @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 fitPredict(drmX: DrmLike[K], drmTarget: DrmLike[K], hyperparameters: (Symbol, Any)*): DrmLike[K]

    Definition Classes
    RegressorFitter

  17. def generateSummaryString[M[K] <: LinearRegressorModel[K]](model: M[K]): String

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

    Definition Classes
    AnyRef → Any

  19. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  20. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  21. var model: RegressorModel[K]

    Definition Classes
    RegressorFitter

  22. def modelPostprocessing[M[K] <: LinearRegressorModel[K]](model: M[K], X: DrmLike[K], drmTarget: DrmLike[K], drmXtXinv: Matrix): M[K]

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

    Definition Classes
    AnyRef

  24. final def notify(): Unit

    Definition Classes
    AnyRef

  25. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

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

    Definition Classes
    AnyRef

  28. def toString(): String

    Definition Classes
    AnyRef → Any

  29. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from RegressorFitter[K]

Inherited from SupervisedFitter[K, RegressorModel[K]]

Inherited from Fitter

Inherited from AnyRef

Inherited from Any

Ungrouped