ml.combust.mleap.core.classification

GBTClassifierModel

case class GBTClassifierModel(trees: Seq[DecisionTreeRegressionModel], treeWeights: Seq[Double], numFeatures: Int, thresholds: Option[Array[Double]] = scala.None) extends ProbabilisticClassificationModel with TreeEnsemble with Serializable with Product

Class for a gradient boost classifier model.

trees

trees in the gradient boost model

treeWeights

weights of each tree

numFeatures

number of features

Linear Supertypes
Product, Equals, Serializable, Serializable, TreeEnsemble, ProbabilisticClassificationModel, ClassificationModel, Model, AnyRef, Any
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  1. GBTClassifierModel
  2. Product
  3. Equals
  4. Serializable
  5. Serializable
  6. TreeEnsemble
  7. ProbabilisticClassificationModel
  8. ClassificationModel
  9. Model
  10. AnyRef
  11. Any
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Instance Constructors

  1. new GBTClassifierModel(trees: Seq[DecisionTreeRegressionModel], treeWeights: Seq[Double], numFeatures: Int, thresholds: Option[Array[Double]] = scala.None)

    trees

    trees in the gradient boost model

    treeWeights

    weights of each tree

    numFeatures

    number of features

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. def apply(features: Vector): Double

    Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

    Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

    features

    feature vector

    returns

    prediction

    Definition Classes
    ClassificationModel

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  9. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  11. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  12. def inputSchema: StructType

    Definition Classes
    ProbabilisticClassificationModel → Model

  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  14. def margin(features: Vector): Double

    Raw prediction for the positive class.

  15. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  16. final def notify(): Unit

    Definition Classes
    AnyRef

  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  18. val numClasses: Int

    Number of classes this model predicts.

    Number of classes this model predicts.

    2 indicates this is a binary classification model. Greater than 2 indicates a multinomial classifier.

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel

  19. val numFeatures: Int

    number of features

    number of features

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel

  20. def numTrees: Int

    Number of trees in the ensemble

    Number of trees in the ensemble

    Definition Classes
    TreeEnsemble

  21. def outputSchema: StructType

    Definition Classes
    ProbabilisticClassificationModel → Model

  22. def predict(features: Vector): Double

    Predict class based on feature vector.

    Predict class based on feature vector.

    features

    feature vector

    returns

    predicted class or probability

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel → ClassificationModel

  23. def predictProbabilities(features: Vector): Vector

    Definition Classes
    ProbabilisticClassificationModel

  24. def predictRaw(features: Vector): Vector

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel

  25. def predictWithProbability(features: Vector): (Double, Double)

    Definition Classes
    ProbabilisticClassificationModel

  26. def probabilityToPrediction(probability: Vector): Double

    Definition Classes
    ProbabilisticClassificationModel

  27. def probabilityToPredictionIndex(probability: Vector): Int

    Definition Classes
    ProbabilisticClassificationModel

  28. def rawToPrediction(raw: Vector): Double

    Definition Classes
    ProbabilisticClassificationModel

  29. def rawToProbability(raw: Vector): Vector

    Definition Classes
    ProbabilisticClassificationModel

  30. def rawToProbabilityInPlace(raw: Vector): Vector

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel

  31. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  32. val thresholds: Option[Array[Double]]

    Definition Classes
    GBTClassifierModel → ProbabilisticClassificationModel

  33. val treeWeights: Seq[Double]

    weights of each tree

    weights of each tree

    Definition Classes
    GBTClassifierModel → TreeEnsemble

  34. val trees: Seq[DecisionTreeRegressionModel]

    trees in the gradient boost model

    trees in the gradient boost model

    Definition Classes
    GBTClassifierModel → TreeEnsemble

  35. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  36. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  37. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from Serializable

Inherited from Serializable

Inherited from TreeEnsemble

Inherited from ProbabilisticClassificationModel

Inherited from ClassificationModel

Inherited from Model

Inherited from AnyRef

Inherited from Any

Ungrouped