GeneralizedLinearRegression.Gaussian$ (Spark 3.5.3 JavaDoc)

Object
- org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$

All Implemented Interfaces:

java.io.Serializable

Enclosing class:

GeneralizedLinearRegression
```
public static class GeneralizedLinearRegression.Gaussian$
extends Object
```
Gaussian exponential family distribution. The default link for the Gaussian family is the identity link.

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

static GeneralizedLinearRegression.Gaussian$ MODULE$
Static reference to the singleton instance of this Scala object.

Fields
Modifier and Type	Field and Description
`static GeneralizedLinearRegression.Gaussian$`	`MODULE$` Static reference to the singleton instance of this Scala object.

Constructor Summary

Constructors
Constructor and Description

Gaussian$()

Constructors
Constructor and Description
`Gaussian$()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`aic(RDD<scala.Tuple3<Object,Object,Object>> predictions, double deviance, double numInstances, double weightSum)` Akaike Information Criterion (AIC) value of the family for a given dataset.
`org.apache.spark.ml.regression.GeneralizedLinearRegression.Link`	`defaultLink()` The default link instance of this family.
`double`	`deviance(double y, double mu, double weight)` Deviance of (y, mu) pair.
`double`	`initialize(double y, double weight)` Initialize the starting value for mu.
`String`	`name()`
`double`	`project(double mu)` Trim the fitted value so that it will be in valid range.
`double`	`variance(double mu)` The variance of the endogenous variable's mean, given the value mu.
`double`	`variancePower()`

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - MODULE$
```
public static final GeneralizedLinearRegression.Gaussian$ MODULE$
```
    Static reference to the singleton instance of this Scala object.
- Constructor Detail
  - Gaussian$
```
public Gaussian$()
```
- Method Detail
  - name
```
public String name()
```
  - defaultLink
```
public org.apache.spark.ml.regression.GeneralizedLinearRegression.Link defaultLink()
```
    The default link instance of this family.
  - initialize
```
public double initialize(double y,
                         double weight)
```
    Initialize the starting value for mu.
  - variance
```
public double variance(double mu)
```
    The variance of the endogenous variable's mean, given the value mu.
  - deviance
```
public double deviance(double y,
                       double mu,
                       double weight)
```
    Deviance of (y, mu) pair.
  - aic
```
public double aic(RDD<scala.Tuple3<Object,Object,Object>> predictions,
                  double deviance,
                  double numInstances,
                  double weightSum)
```
    Akaike Information Criterion (AIC) value of the family for a given dataset.
    
    Parameters:
    
    predictions - an RDD of (y, mu, weight) of instances in evaluation dataset
    
    deviance - the deviance for the fitted model in evaluation dataset
    
    numInstances - number of instances in evaluation dataset
    
    weightSum - weights sum of instances in evaluation dataset
    
    Returns:
    
    (undocumented)
  - project
```
public double project(double mu)
```
    Trim the fitted value so that it will be in valid range.
  - variancePower
```
public double variancePower()
```

Class GeneralizedLinearRegression.Gaussian$

Field Summary

Constructor Summary

Method Summary

Methods inherited from class Object

Field Detail

MODULE$

Constructor Detail

Gaussian$

Method Detail

name

defaultLink

initialize

variance

deviance

aic

project

variancePower