org.apache.mahout.math.algorithms.regression

OrdinaryLeastSquaresModel

class OrdinaryLeastSquaresModel[K] extends LinearRegressorModel[K]

Linear Supertypes
LinearRegressorModel[K], RegressorModel[K], SupervisedModel[K], Model, Serializable, Serializable, AnyRef, Any
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Inherited
  1. OrdinaryLeastSquaresModel
  2. LinearRegressorModel
  3. RegressorModel
  4. SupervisedModel
  5. Model
  6. Serializable
  7. Serializable
  8. AnyRef
  9. Any
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Instance Constructors

  1. new OrdinaryLeastSquaresModel()

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
    RegressorModel

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. var beta: Vector

    Definition Classes
    LinearRegressorModel

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  10. var degreesFreedom: Int

    Definition Classes
    LinearRegressorModel

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

    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  13. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  15. def getTestResult[T](testSymbol: Symbol): Option[T]

    Syntatictic sugar for fetching test results.

    Syntatictic sugar for fetching test results. Will Return test result if it exists, otherwise None

    T

    - The Type

    testSymbol

    - symbol of the test result to fetch, e.g. 'mse

    returns

    Definition Classes
    RegressorModel

  16. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  17. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  18. var mse: Double

    Definition Classes
    RegressorModel

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

    Definition Classes
    AnyRef

  20. final def notify(): Unit

    Definition Classes
    AnyRef

  21. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  22. def predict(drmPredictors: DrmLike[K]): DrmLike[K]

    Definition Classes
    OrdinaryLeastSquaresModel → RegressorModel

  23. var pval: Vector

    Definition Classes
    LinearRegressorModel

  24. var r2: Double

    Definition Classes
    RegressorModel

  25. var se: Vector

    Definition Classes
    LinearRegressorModel

  26. var summary: String

    Definition Classes
    Model

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

    Definition Classes
    AnyRef

  28. var tScore: Vector

    Definition Classes
    LinearRegressorModel

  29. var testResults: Map[Symbol, Any]

    Definition Classes
    SupervisedModel

  30. def toString(): String

    Definition Classes
    AnyRef → Any

  31. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from LinearRegressorModel[K]

Inherited from RegressorModel[K]

Inherited from SupervisedModel[K]

Inherited from Model

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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