org.apache.spark.mllib.tree.loss

Loss

trait Loss extends Serializable

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

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@Since( "1.2.0" ) @DeveloperApi()
Source
Loss.scala
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AbsoluteError, LogLoss, SquaredError
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  1. abstract def gradient(prediction: Double, label: Double): Double

    Method to calculate the gradients for the gradient boosting calculation.

    Method to calculate the gradients for the gradient boosting calculation.

    prediction

    Predicted feature

    label

    true label.

    returns

    Loss gradient.

    Annotations
    @Since( "1.2.0" )

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  8. def computeError(model: TreeEnsembleModel, data: RDD[LabeledPoint]): Double

    Method to calculate error of the base learner for the gradient boosting calculation.

    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.

    model

    Model of the weak learner.

    data

    Training dataset: RDD of org.apache.spark.mllib.regression.LabeledPoint.

    returns

    Measure of model error on data

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    @Since( "1.2.0" )

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