scalation
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scalation/scalation/scalation.modeling/RegressionTreeGB

RegressionTreeGB

scalation.modeling.RegressionTreeGB
See theRegressionTreeGB companion class
object RegressionTreeGB

The RegressionTreeGB companion object defines hyper-parameters and provides a factory methods for creating gradient boosted regression trees.

Attributes

Companion
class
Graph
Supertypes
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): RegressionTreeGB

Create a RegressionTreeGB object that uses Gradient Boosting on RegressionTree. One Tree is included in the model at a time wisely chosen for reducing gradient.

Create a RegressionTreeGB object that uses Gradient Boosting on RegressionTree. One Tree is included in the model at a time wisely chosen for reducing gradient.

Value parameters

col

the designated response column (defaults to the last column)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters for the model (defaults to RegressionTree.hp)

xy

the combined data-response matrix

Attributes

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

Create a RegressionTreeGB object that uses Gradient Boosting on RegressionTree. One Tree is included in the model at a time wisely chosen for reducing gradient.

Create a RegressionTreeGB object that uses Gradient Boosting on RegressionTree. One Tree is included in the model at a time wisely chosen for reducing gradient.

Value parameters

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters for the model (defaults to RegressionTree.hp)

x

the input/data matrix

y

the output/response vector

Attributes

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