org.apache.spark.mllib.tree.model
GradientBoostedTreesModel
Companion class GradientBoostedTreesModel
object GradientBoostedTreesModel extends Loader[GradientBoostedTreesModel] with Serializable
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- @Since( "1.3.0" )
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- treeEnsembleModels.scala
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def
computeInitialPredictionAndError(data: RDD[LabeledPoint], initTreeWeight: Double, initTree: DecisionTreeModel, loss: Loss): RDD[(Double, Double)]
Compute the initial predictions and errors for a dataset for the first iteration of gradient boosting.
Compute the initial predictions and errors for a dataset for the first iteration of gradient boosting.
- returns
an RDD with each element being a zip of the prediction and error corresponding to every sample.
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- @Since( "1.4.0" )
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def
load(sc: SparkContext, path: String): GradientBoostedTreesModel
- sc
Spark context used for loading model files.
- path
Path specifying the directory to which the model was saved.
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Model instance
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- GradientBoostedTreesModel → Loader
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- @Since( "1.3.0" )
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def
updatePredictionError(data: RDD[LabeledPoint], predictionAndError: RDD[(Double, Double)], treeWeight: Double, tree: DecisionTreeModel, loss: Loss): RDD[(Double, Double)]
Update a zipped predictionError RDD (as obtained with computeInitialPredictionAndError)
Update a zipped predictionError RDD (as obtained with computeInitialPredictionAndError)
- returns
an RDD with each element being a zip of the prediction and error corresponding to each sample.
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- @Since( "1.4.0" )
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