The Regression companion object provides factory methods for creating regression models.
Attributes
- Companion
- class
- Graph
-
- Supertypes
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class Objecttrait Matchableclass Any
- Self type
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Regression.type
Members list
Value members
Concrete methods
Create a Regression object from a combined data-response matrix.
Create a Regression object from a combined data-response matrix.
Value parameters
- col
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the designated response column (defaults to the last column)
- fname
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the feature/variable names (defaults to null)
- hparam
-
the hyper-parameters (defaults to hp)
- xy
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the combined data-response matrix (predictors and response)
Attributes
Create a Regression object from a data matrix and a response vector. This method provides data rescaling of x. However, rescaling of y may be needed for Regularized Regression and Neural Networks.
Create a Regression object from a data matrix and a response vector. This method provides data rescaling of x. However, rescaling of y may be needed for Regularized Regression and Neural Networks.
Value parameters
- fname
-
the feature/variable names (defaults to null)
- hparam
-
the hyper-parameters (defaults to hp)
- x
-
the data/input m-by-n matrix (augment with a first column of ones to include intercept in model)
- y
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the response/output m-vector
Attributes
Concrete fields
Base hyper-parameter specification for Regression
Base hyper-parameter specification for Regression
Attributes
Main metrics for regression type problems, e.g., used in PlotM
Main metrics for regression type problems, e.g., used in PlotM