object QuadXRegression4TSy extends ModelFactory
The QuadXRegression4TSy companion object provides factory functions and functions
for creating functional forms.
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- 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
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- ModelFactory
- def apply(y: VectoD, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique = QR): QuadXRegression4TSy
Create a
QuadXRegression4TSyobject from a response vector.Create a
QuadXRegression4TSyobject from a response vector. This factory function provides data rescaling.- y
the output/response m-vector (before expansion)
- fname
the feature/variable names (if null, use x_j's)
- hparam
the hyper-parameters for the model/network
- technique
the technique used to solve for b in x.t*x*b = x.t*y
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ModelFactory
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- 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
Regressionwith intercept).Given a vector/point 'v', compute the values for all of its forms/terms, returning them as a vector (assumes
Regressionwith 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
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- def numTerms(k: Int): Int
The number of terms include current value and lag one value.
The number of terms include current value and lag one value. when there are no cross-terms.
- k
number of features/predictor variables (not counting intercept)
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- QuadXRegression4TSy → ModelFactory
- 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
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- def rescaleOff(): Unit
Turn rescaling off.
Turn rescaling off.
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- def rescaleOn(): Unit
Turn rescaling on.
Turn rescaling on.
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