object CubicRegression extends ModelFactory
The CubicRegression
companion object provides methods 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
- Definition Classes
- ModelFactory
- def apply(x: MatriD, y: VectoD, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): CubicRegression
Create a
CubicRegression
object from a data matrix and a response vector.Create a
CubicRegression
object from a data matrix and a response vector. This factory function provides data rescaling.- x
the initial data/input matrix (before quadratic term expansion)
- y
the response/output m-vector
- fname
the feature/variable names (use null for default)
- hparam
the hyper-parameters (use null for default)
- technique
the technique used to solve for b in x.t*x*b = x.t*y (use OR for default)
- See also
ModelFactory
- def apply(xy: MatriD, fname: Strings = null, hparam: HyperParameter = null, technique: RegTechnique.RegTechnique = QR): CubicRegression
Create a
CubicRegression
object from a combined data-response matrix.Create a
CubicRegression
object from a combined data-response matrix.- xy
the initial combined data-response matrix (before quadratic term expansion)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
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- val drp: (Null, Null, RegTechnique.Value)
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- def forms(v: VectoD, k: Int, nt: Int): VectoD
Given a vector/point 'p', compute the values for all of its cubic, quadratic, linear and constant forms/terms, returning them as a vector.
Given a vector/point 'p', compute the values for all of its cubic, quadratic, linear and constant forms/terms, returning them as a vector. for 1D: v = (x_0) => 'VectorD (1, x_0, x_02, x_03)' for 2D: v = (x_0, x_1) => 'VectorD (1, x_0, x_02, x_03, x_1, x_12, x_13, x_0*x_1)'
- v
the source vector/point for creating forms/terms
- k
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 cubic, quadratic, linear and constant forms/terms (4, 8, 13, 19, ...).
The number of cubic, quadratic, linear and constant forms/terms (4, 8, 13, 19, ...).
- k
number of features/predictor variables (not counting intercept)
- Definition Classes
- CubicRegression → 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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- ModelFactory
- def rescaleOn(): Unit
Turn rescaling on.
Turn rescaling on.
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