RidgeRegression

scalation.modeling.RidgeRegression
See theRidgeRegression companion class
object RidgeRegression extends Regularized

The RidgeRegression companion object defines hyper-parameters and provides factory methods creating ridge regression models.

Attributes

Companion
class
Graph
Supertypes
trait Regularized
class Object
trait Matchable
class Any
Self type

Members list

Value members

Concrete methods

def apply(xy: MatrixD, fname: Array[String] = ..., hparam: HyperParameter = ...)(col: Int = ...): RidgeRegression

Create a Ridge Regression from a combined data matrix. This function centers the data.

Create a Ridge Regression from a combined data matrix. This function centers the data.

Value parameters

col

the designated response column (defaults to the last column)

fname

the feature/variable names (defaults to null)

hparam

the shrinkage hyper-parameter (0 => OLS) in the penalty term lambda * b dot b

xy

the un-centered data/input m-by-n matrix, NOT augmented with a first column of ones and the un-centered response m-vector (combined)

Attributes

def center(x: MatrixD, y: VectorD, fname: Array[String] = ..., hparam: HyperParameter = ...): RidgeRegression

Create a Ridge Regression from a data matrix and response vector. This function centers the data.

Create a Ridge Regression from a data matrix and response vector. This function centers the data.

Value parameters

fname

the feature/variable names (defaults to null)

hparam

the shrinkage hyper-parameter (0 => OLS) in the penalty term 'lambda * b dot b'

x

the un-centered data/input m-by-n matrix, NOT augmented with a first column of ones

y

the un-centered response/output vector

Attributes

Fix the smape calculation for be in the original rather than centered scale.

Fix the smape calculation for be in the original rather than centered scale.

Value parameters

mod

the model being used

qof

the Quality-of-Fit metrics

y

the response vector in the original scale

Attributes

def rescale(x: MatrixD, y: VectorD, fname: Array[String] = ..., hparam: HyperParameter = ...): RidgeRegression

Create a RidgeRegression object from a data matrix and a response vector. This method provides data rescaling of x and centering of y.

Create a RidgeRegression object from a data matrix and a response vector. This method provides data rescaling of x and centering of y.

Value parameters

fname

the feature/variable names (defaults to null)

hparam

the shrinkage hyper-parameter (0 => OLS) in the penalty term 'lambda * b dot b'

x

the un-centered data/input m-by-n matrix, NOT augmented with a first column of ones

y

the un-centered response/output vector

Attributes

Concrete fields

Base hyper-parameter specification for RidgeRegression and other regularized regression classes

Base hyper-parameter specification for RidgeRegression and other regularized regression classes

Attributes