org.apache.spark.mllib.tree.loss
Class LogLoss

Object
  extended by org.apache.spark.mllib.tree.loss.LogLoss
All Implemented Interfaces:
java.io.Serializable, Loss

public class LogLoss
extends Object
implements Loss

:: DeveloperApi :: Class for log loss calculation (for classification). This uses twice the binomial negative log likelihood, called "deviance" in Friedman (1999).

The log loss is defined as: 2 log(1 + exp(-2 y F(x))) where y is a label in {-1, 1} and F(x) is the model prediction for features x.

See Also:
Serialized Form

Constructor Summary
LogLoss()
           
 
Method Summary
static double gradient(double prediction, double label)
          Method to calculate the loss gradients for the gradient boosting calculation for binary classification The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))
 
Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.apache.spark.mllib.tree.loss.Loss
computeError, computeError, gradient
 

Constructor Detail

LogLoss

public LogLoss()
Method Detail

gradient

public static double gradient(double prediction,
                              double label)
Method to calculate the loss gradients for the gradient boosting calculation for binary classification The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))

Parameters:
prediction - Predicted label.
label - True label.
Returns:
Loss gradient