org.allenai.nlpstack.parse.poly.decisiontree

RandomForestTrainer

Related Doc: package decisiontree

class RandomForestTrainer extends ProbabilisticClassifierTrainer

A RandomForestTrainer trains a RandomForest from a set of feature vectors.

Linear Supertypes
ProbabilisticClassifierTrainer, (FeatureVectorSource) ⇒ ProbabilisticClassifier, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. RandomForestTrainer
  2. ProbabilisticClassifierTrainer
  3. Function1
  4. AnyRef
  5. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new RandomForestTrainer(validationPercentage: Float, numDecisionTrees: Int, featuresExaminedPerNode: Float, gainMetric: InformationGainMetric, useBagging: Boolean = false, maximumDepthPerTree: Int = Integer.MAX_VALUE, numThreads: Int = 1)

    validationPercentage

    percentage of feature vectors to hold out for decision tree validation

    numDecisionTrees

    desired number of decision trees in the forest

    featuresExaminedPerNode

    during decision tree induction, desired percentage of randomly selected features to consider at each node

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. def andThen[A](g: (ProbabilisticClassifier) ⇒ A): (FeatureVectorSource) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  5. def apply(data: FeatureVectorSource): ProbabilisticClassifier

    Induces a RandomForest from a set of feature vectors.

    Induces a RandomForest from a set of feature vectors.

    data

    a set of feature vectors to use for training

    returns

    the induced random forest

    Definition Classes
    RandomForestTrainer → Function1

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

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

  8. def compose[A](g: (A) ⇒ FeatureVectorSource): (A) ⇒ ProbabilisticClassifier

    Definition Classes
    Function1
    Annotations
    @unspecialized()

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

    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  11. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  19. def toString(): String

    Definition Classes
    Function1 → AnyRef → Any

  20. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ProbabilisticClassifierTrainer

Inherited from (FeatureVectorSource) ⇒ ProbabilisticClassifier

Inherited from AnyRef

Inherited from Any

Ungrouped