ml.combust.mleap.core.classification

RandomForestClassifierModel

case class RandomForestClassifierModel(trees: Seq[DecisionTreeClassifierModel], treeWeights: Seq[Double], numFeatures: Int, numClasses: Int) extends MultinomialClassificationModel with TreeEnsemble with Serializable with Product

Class for random forest classification models.

trees

trees of the random forest

numFeatures

number of features in feature vector

numClasses

number of predictable classes

Linear Supertypes
Product, Equals, Serializable, Serializable, TreeEnsemble, MultinomialClassificationModel, ClassificationModel, AnyRef, Any
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  1. RandomForestClassifierModel
  2. Product
  3. Equals
  4. Serializable
  5. Serializable
  6. TreeEnsemble
  7. MultinomialClassificationModel
  8. ClassificationModel
  9. AnyRef
  10. Any
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Instance Constructors

  1. new RandomForestClassifierModel(trees: Seq[DecisionTreeClassifierModel], treeWeights: Seq[Double], numFeatures: Int, numClasses: Int)

    trees

    trees of the random forest

    numFeatures

    number of features in feature vector

    numClasses

    number of predictable classes

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. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  14. final def notify(): Unit

    Definition Classes
    AnyRef

  15. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  16. val numClasses: Int

    number of predictable classes

    number of predictable classes

    Definition Classes
    RandomForestClassifierModel → MultinomialClassificationModel

  17. val numFeatures: Int

    number of features in feature vector

  18. def numTrees: Int

    Number of trees in the ensemble

    Number of trees in the ensemble

    Definition Classes
    TreeEnsemble

  19. 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
    MultinomialClassificationModel → ClassificationModel

  20. def predictProbabilities(features: Vector): Vector

    Definition Classes
    MultinomialClassificationModel

  21. def predictRaw(raw: Vector): Vector

    Definition Classes
    RandomForestClassifierModel → MultinomialClassificationModel

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

    Definition Classes
    MultinomialClassificationModel

  23. def probabilityToPrediction(probability: Vector): Double

    Definition Classes
    MultinomialClassificationModel

  24. def rawToPrediction(raw: Vector): Double

    Definition Classes
    MultinomialClassificationModel

  25. def rawToProbability(raw: Vector): Vector

    Definition Classes
    MultinomialClassificationModel

  26. def rawToProbabilityInPlace(raw: Vector): Vector

    Definition Classes
    RandomForestClassifierModel → MultinomialClassificationModel

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

    Definition Classes
    AnyRef

  28. def thresholds: Option[Array[Double]]

    Definition Classes
    MultinomialClassificationModel

  29. val treeWeights: Seq[Double]

    Weights for each tree.

    Weights for each tree.

    Definition Classes
    RandomForestClassifierModel → TreeEnsemble

  30. val trees: Seq[DecisionTreeClassifierModel]

    trees of the random forest

    trees of the random forest

    Definition Classes
    RandomForestClassifierModel → TreeEnsemble

  31. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  33. 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 MultinomialClassificationModel

Inherited from ClassificationModel

Inherited from AnyRef

Inherited from Any

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