public class LogLoss
extends Object
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 and Description | 
|---|
| LogLoss() | 
| Modifier and Type | Method and 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))) | 
public static double gradient(double prediction,
                              double label)
prediction - Predicted label.label - True label.