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scalation.analytics

ModelFactory

trait ModelFactory extends Error

The ModelFactory trait is intended for use in Model factory objects. It supports expansion of the data matrix and rescaling of data values. When the 'rescale' flag is on/true, the companion object factory 'apply' functions should rescale or normalize the data appropriately to the particular modeling technique (or even to the level of the activation function used). In ScalaTion, model constructors do not rescale, but 'apply' functions that call model constructors need to provide this option. For example,

val model1 = new Regression (x, y, fname, hparam, technique) val model2 = Regression (x, y, fname, hparam, technique)

'model1' will not have its data rescaled, while 'model2' will.

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  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. 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

  5. final def asInstanceOf[T0]: T0
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  6. def clone(): AnyRef
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  7. final def eq(arg0: AnyRef): Boolean
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  9. final def flaw(method: String, message: String): Unit
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  10. 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

  11. final def getClass(): Class[_]
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  12. def hashCode(): Int
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  13. final def isInstanceOf[T0]: Boolean
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  14. final def ne(arg0: AnyRef): Boolean
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  15. final def notify(): Unit
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  16. final def notifyAll(): Unit
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  17. 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)

  18. 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
  19. def rescaleOff(): Unit

    Turn rescaling off.

  20. def rescaleOn(): Unit

    Turn rescaling on.

  21. final def synchronized[T0](arg0: ⇒ T0): T0
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  1. def finalize(): Unit
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