object Regression extends ModelFactory
The Regression companion object provides factory apply functions and a testing method.
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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): Regression
Create a
Regressionobject from a data matrix and a response vector.Create a
Regressionobject from a data matrix and a response vector. This factory function provides data rescaling.- x
the data/input m-by-n matrix (augment with a first column of ones to include intercept in model)
- 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): Regression
Create a
Regressionobject from a combined data-response matrix.Create a
Regressionobject from a combined data-response matrix. The last column is assumed to be the response column.- xy
the combined data-response matrix (predictors and response)
- fname
the feature/variable names
- 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(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/parameters in the model (assumes
Regressionwith intercept.The number of terms/parameters in the model (assumes
Regressionwith intercept. Override for expanded columns, e.g.,QuadRegression.- k
the number of features/predictor variables (not counting intercept)
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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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def
test(x: MatriD, y: VectoD, z: VectoD, fname: Strings = null): Unit
Test the various regression techniques.
Test the various regression techniques.
- x
the data/input matrix
- y
the response/output vector
- z
a vector to predict
- fname
the names of features/variable
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