Packages

  • package root
    Definition Classes
    root
  • package org
    Definition Classes
    root
  • package apache
    Definition Classes
    org
  • package spark
    Definition Classes
    apache
  • package mllib

    RDD-based machine learning APIs (in maintenance mode).

    RDD-based machine learning APIs (in maintenance mode).

    The spark.mllib package is in maintenance mode as of the Spark 2.0.0 release to encourage migration to the DataFrame-based APIs under the org.apache.spark.ml package. While in maintenance mode,

    • no new features in the RDD-based spark.mllib package will be accepted, unless they block implementing new features in the DataFrame-based spark.ml package;
    • bug fixes in the RDD-based APIs will still be accepted.

    The developers will continue adding more features to the DataFrame-based APIs in the 2.x series to reach feature parity with the RDD-based APIs. And once we reach feature parity, this package will be deprecated.

    Definition Classes
    spark
    See also

    SPARK-4591 to track the progress of feature parity

  • package tree

    This package contains the default implementation of the decision tree algorithm, which supports:

    This package contains the default implementation of the decision tree algorithm, which supports:

    • binary classification,
    • regression,
    • information loss calculation with entropy and Gini for classification and variance for regression,
    • both continuous and categorical features.
    Definition Classes
    mllib
  • package model
    Definition Classes
    tree
  • DecisionTreeModel
  • GradientBoostedTreesModel
  • InformationGainStats
  • Node
  • Predict
  • RandomForestModel
  • Split

object GradientBoostedTreesModel extends Loader[GradientBoostedTreesModel] with Serializable

Annotations
@Since( "1.3.0" )
Linear Supertypes
Serializable, Serializable, Loader[GradientBoostedTreesModel], AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. GradientBoostedTreesModel
  2. Serializable
  3. Serializable
  4. Loader
  5. AnyRef
  6. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  6. 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.

    Annotations
    @Since( "1.4.0" )
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  10. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  12. 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.

    returns

    Model instance

    Definition Classes
    GradientBoostedTreesModel → Loader
    Annotations
    @Since( "1.3.0" )
  13. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  15. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  16. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  17. def toString(): String
    Definition Classes
    AnyRef → Any
  18. 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.

    Annotations
    @Since( "1.4.0" )
  19. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  20. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  21. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Serializable

Inherited from Loader[GradientBoostedTreesModel]

Inherited from AnyRef

Inherited from Any

Ungrouped