TranRegression

scalation.modeling.TranRegression
See theTranRegression companion class

The TranRegression companion object provides transformation and inverse transformation function based on the parameter λ. It support the family of Box-Cox and Yeo-Johnson Transformations.

Attributes

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

Members list

Value members

Concrete methods

def `λ_=`(`λ_`: Double): Unit
def apply(xy: MatrixD, fname: Array[String] = ..., hparam: HyperParameter = ..., yℱ: Transform = ...): TranRegression

Create a TranRegression with from a combined matrix.

Create a TranRegression with from a combined matrix.

Value parameters

fname

the feature/variable names

hparam

the hyper-parameters

xy

the combined data/input and response/output matrix

yℱ

the transformation applied to y (e.g., Boxcox)

Attributes

def john_yeo(z: Double): Double

Inverse transform z using the Yeo-Johnson transformation.

Inverse transform z using the Yeo-Johnson transformation.

Value parameters

z

the value to be inverse transformed

Attributes

def yeo_john(y: Double): Double

Transform y using the Yeo-Johnson transformation.

Transform y using the Yeo-Johnson transformation.

Value parameters

y

the value to be transformed

Attributes

inline def λ: Double