Developer API

org.apache.spark.mllib.tree.loss

Class SquaredError

Object

org.apache.spark.mllib.tree.loss.SquaredError

public class SquaredError
extends Object

Class for squared error loss calculation.

The squared (L2) error is defined as: (y - F(x))**2 where y is the label and F(x) is the model prediction for features x.

Constructor Summary

Constructors

Constructor and Description
SquaredError()

Method Summary

Modifier and Type	Method and Description
static double	gradient(double prediction, double label) Method to calculate the gradients for the gradient boosting calculation for least squares error calculation.

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SquaredError

public SquaredError()

Method Detail

gradient

public static double gradient(double prediction,
                              double label)

Method to calculate the gradients for the gradient boosting calculation for least squares error calculation. The gradient with respect to F(x) is: - 2 (y - F(x))

Parameters:

prediction - Predicted label.

label - True label.

Returns:

Loss gradient