Package org.apache.spark.mllib.tree.loss
Class LogLoss
Object
org.apache.spark.mllib.tree.loss.LogLoss
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.
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionstatic 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)))
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Constructor Details
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LogLoss
public LogLoss()
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Method Details
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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
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