scalation
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scalation/scalation/scalation.modeling/RegressionCat

RegressionCat

scalation.modeling.RegressionCat
See theRegressionCat companion class
object RegressionCat

The RegressionCat companion object provides factory methods and other helper methods.

Attributes

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

Members list

Value members

Concrete methods

def apply(xt: MatrixD, y: VectorD, nCat: Int, fname: Array[String], hparam: HyperParameter): RegressionCat

Create a RegressionCat object from a single data matrix.

Create a RegressionCat object from a single data matrix.

Value parameters

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defualts to Regression.hp)

nCat

the index at which the categorical variables start in xt requires the cont vars to be first, followed by the cat vars

xt

the data/input matrix of continuous and categorical variables

y

the response/output vector

Attributes

def dummyVar(t: VectorI, shf: VectorI, tmx: VectorI): VectorD

Assign values for dummy variables based on a single categorical/treatment vector t.

Assign values for dummy variables based on a single categorical/treatment vector t.

Value parameters

sht

the amount to shift the vector

t

the categorical/treatment vector

tmx

the maximum vector categorical/treatment after shifting

Attributes

See also

Variable Note: To maintain consistency Variable is the only place where values for dummy variables should be set.

def dummyVars(t: MatrixI): MatrixD

Assign values for the dummy variables based on the categorical/treatment vector t.

Assign values for the dummy variables based on the categorical/treatment vector t.

Value parameters

t

the categorical/treatment level matrix

Attributes

See also

Variable Note: To maintain consistency Variable is the only place where values for dummy variables should be set

def get_shift_tmax: (VectorI, VectorI)

Return the shift in categorical/treatment variables to make tihem start at zero as well as the maximum values after shifting. Must call dummyVars first.

Return the shift in categorical/treatment variables to make tihem start at zero as well as the maximum values after shifting. Must call dummyVars first.

Attributes

def rescale(x: MatrixD, t: MatrixI, y: VectorD, fname: Array[String], hparam: HyperParameter): RegressionCat

Create a RegressionCat object from a continuous a data matrix and a categorical data matrix. This method does rescaling.

Create a RegressionCat object from a continuous a data matrix and a categorical data matrix. This method does rescaling.

Value parameters

fname

the feature/variable names (defualts to null)

hparam

the hyper-parameters (defualts to Regression.hp)

t

the treatment/categorical variable matrix

x

the data/input matrix of continuous variables

y

the response/output vector

Attributes

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