org.apache.spark.mllib.tree.loss

Class SquaredError

java.lang.Object

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

All Implemented Interfaces:

java.io.Serializable, Loss

public class SquaredError
extends java.lang.Object
implements Loss

:: DeveloperApi :: 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.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SquaredError()

Method Summary

Methods

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 java.lang.Object

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

Methods inherited from interface org.apache.spark.mllib.tree.loss.Loss

computeError, computeError, gradient

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