Method to calculate loss when the predictions are already known.
Method to calculate loss when the predictions are already known.
Predicted label.
True label.
Measure of model error on datapoint.
Returns the estimated probability of a label of 1.
Returns the estimated probability of a label of 1.0.
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)))
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.