org.apache.spark.mllib.tree.loss
Class LogLoss
Object
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
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 |
LogLoss
public LogLoss()
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