Class/Object

frameless.ml.classification

TypedRandomForestClassifier

Related Docs: object TypedRandomForestClassifier | package classification

Permalink

final class TypedRandomForestClassifier[Inputs] extends TypedEstimator[Inputs, Outputs, RandomForestClassificationModel]

Random Forest learning algorithm for classification. It supports both binary and multiclass labels, as well as both continuous and categorical features.

Linear Supertypes
TypedEstimator[Inputs, Outputs, RandomForestClassificationModel], AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. TypedRandomForestClassifier
  2. TypedEstimator
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

  5. def clone(): AnyRef

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

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

    Permalink
    Definition Classes
    AnyRef

  7. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  8. val estimator: RandomForestClassifier

    Permalink
    Definition Classes
    TypedRandomForestClassifier → TypedEstimator

  9. def finalize(): Unit

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

  10. def fit[T, F[_]](ds: TypedDataset[T])(implicit smartProject: SmartProject[T, Inputs], F: SparkDelay[F]): F[AppendTransformer[Inputs, Outputs, RandomForestClassificationModel]]

    Permalink
    Definition Classes
    TypedEstimator

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

    Permalink
    Definition Classes
    AnyRef → Any

  12. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  13. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

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

    Permalink
    Definition Classes
    AnyRef

  15. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  17. def setFeatureSubsetStrategy(value: FeatureSubsetStrategy): TypedRandomForestClassifier[Inputs]

    Permalink

  18. def setMaxBins(value: Int): TypedRandomForestClassifier[Inputs]

    Permalink

  19. def setMaxDepth(value: Int): TypedRandomForestClassifier[Inputs]

    Permalink

  20. def setMaxMemoryInMB(value: Int): TypedRandomForestClassifier[Inputs]

    Permalink

  21. def setMinInfoGain(value: Double): TypedRandomForestClassifier[Inputs]

    Permalink

  22. def setMinInstancesPerNode(value: Int): TypedRandomForestClassifier[Inputs]

    Permalink

  23. def setNumTrees(value: Int): TypedRandomForestClassifier[Inputs]

    Permalink

  24. def setSubsamplingRate(value: Double): TypedRandomForestClassifier[Inputs]

    Permalink

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

    Permalink
    Definition Classes
    AnyRef

  26. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any

  27. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TypedEstimator[Inputs, Outputs, RandomForestClassificationModel]

Inherited from AnyRef

Inherited from Any

Ungrouped