Packages

object NonLinRegression extends ModelFactory

The NonLinRegression companion object provides factory methods for buidling perceptrons. Note, 'rescale' is defined in ModelFactory in Model.scala.

Linear Supertypes
ModelFactory, Error, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. NonLinRegression
  2. ModelFactory
  3. Error
  4. AnyRef
  5. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

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. def allForms(x: MatriD): MatriD

    Create all forms/terms for each row/point placing them in a new matrix.

    Create all forms/terms for each row/point placing them in a new matrix.

    x

    the original un-expanded input/data matrix

    Definition Classes
    ModelFactory
  5. def apply(x: MatriD, y: VectoD, f: FunctionP2S, b_init: VectorD, fname: Strings, hparam: HyperParameter): NonLinRegression

    Create a NonLinRegression with automatic rescaling from a data matrix and response vector.

    Create a NonLinRegression with automatic rescaling from a data matrix and response vector.

    x

    the data/input matrix

    y

    the response/output vector

    f

    the non-linear function f(x, b) to fit

    b_init

    the initial guess for the parameter vector b

    fname

    the feature/variable names

    hparam

    the hyper-parameters (currently has none)

  6. def apply(xy: MatriD, f: FunctionP2S, b_init: VectorD, fname: Strings = null, hparam: HyperParameter = null): NonLinRegression

    Create a NonLinRegression with automatic rescaling from a combined data matrix.

    Create a NonLinRegression with automatic rescaling from a combined data matrix.

    xy

    the combined data/input and response/output matrix

    f

    the non-linear function f(x, b) to fit

    b_init

    the initial guess for the parameter vector b

    fname

    the feature/variable names

    hparam

    the hyper-parameters (currently has none)

  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  9. val drp: (Null, Null)
  10. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  12. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  13. def forms(xi: VectoD, k: Int, nt: Int): VectoD

    Given a vector/point 'v', compute the values for all of its forms/terms, returning them as a vector (assumes Regression with intercept).

    Given a vector/point 'v', compute the values for all of its forms/terms, returning them as a vector (assumes Regression with intercept). Override for expanded columns, e.g., QuadRegression.

    xi

    the vector/point (i-th row of x) for creating forms/terms

    k

    the number of features/predictor variables (not counting intercept)

    nt

    the number of terms

    Definition Classes
    ModelFactory
  14. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  20. def numTerms(k: Int): Int

    The number of terms/parameters in the model (assumes Regression with intercept.

    The number of terms/parameters in the model (assumes Regression with intercept. Override for expanded columns, e.g., QuadRegression.

    k

    the number of features/predictor variables (not counting intercept)

    Definition Classes
    ModelFactory
  21. val rescale: Boolean

    The 'rescale' flag indicated whether the data is to be rescaled/normalized

    The 'rescale' flag indicated whether the data is to be rescaled/normalized

    Attributes
    protected
    Definition Classes
    ModelFactory
  22. def rescaleOff(): Unit

    Turn rescaling off.

    Turn rescaling off.

    Definition Classes
    ModelFactory
  23. def rescaleOn(): Unit

    Turn rescaling on.

    Turn rescaling on.

    Definition Classes
    ModelFactory
  24. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  25. def toString(): String
    Definition Classes
    AnyRef → Any
  26. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  28. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from ModelFactory

Inherited from Error

Inherited from AnyRef

Inherited from Any

Ungrouped