Class LogLoss

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

public class LogLoss extends Object
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.

  • Constructor Summary

    Constructors
    Constructor
    Description
     
  • Method Summary

    Modifier and Type
    Method
    Description
    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 java.lang.Object

    equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
  • Constructor Details

    • LogLoss

      public LogLoss()
  • Method Details

    • 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