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.