org.apache.spark.mllib.tree.loss

Interface Loss

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

AbsoluteError, LogLoss, SquaredError

public interface Loss
extends scala.Serializable

:: DeveloperApi :: Trait for adding "pluggable" loss functions for the gradient boosting algorithm.

Method Summary

Methods

Modifier and Type	Method and Description
double	computeError(TreeEnsembleModel model, RDD<LabeledPoint> data) Method to calculate error of the base learner for the gradient boosting calculation.
double	gradient(TreeEnsembleModel model, LabeledPoint point) Method to calculate the gradients for the gradient boosting calculation.

Method Detail

gradient

double gradient(TreeEnsembleModel model,
              LabeledPoint point)

Method to calculate the gradients for the gradient boosting calculation.

Parameters:

model - Model of the weak learner.

point - Instance of the training dataset.

Returns:

Loss gradient.

computeError

double computeError(TreeEnsembleModel model,
                  RDD<LabeledPoint> data)

Method to calculate error of the base learner for the gradient boosting calculation. Note: This method is not used by the gradient boosting algorithm but is useful for debugging purposes.

Parameters:

model - Model of the weak learner.

data - Training dataset: RDD of LabeledPoint.

Returns:

Measure of model error on data