object QuadRegression extends ModelFactory
The QuadRegression 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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def
apply(x: MatriD, y: VectoD, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): QuadRegression
Create a
QuadRegressionobject from a data matrix and a response vector.Create a
QuadRegressionobject 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
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def
apply(xy: MatriD, fname: Strings = null, hparam: HyperParameter = null, technique: RegTechnique.RegTechnique = QR): QuadRegression
Create a
QuadRegressionobject from a combined data-response matrix.Create a
QuadRegressionobject 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 'v', compute the values for all of its quadratic, linear and constant forms/terms, returning them as a vector.
Given a vector/point 'v', compute the values for all of its quadratic, linear and constant forms/terms, returning them as a vector. No interaction/cross-terms. for 1D: v = (x_0) => 'VectorD (1, x_0, x_02)' for 2D: v = (x_0, x_1) => 'VectorD (1, x_0, x_1, x_02, x_1^2)'
- v
the vector/point (i-th row of x) for creating forms/terms
- k
number of features/predictor variables (not counting intercept) [not used]
- nt
the number of terms
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def
numTerms(k: Int): Int
The number of quadratic, linear and constant forms/terms (1, 3, 5, 7, ...).
The number of quadratic, linear and constant forms/terms (1, 3, 5, 7, ...). when there are no cross-terms.
- k
number of features/predictor variables (not counting intercept)
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- QuadRegression → ModelFactory
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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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