cc.factorie.app.classify.backend

RandomForestMulticlassTrainer

class RandomForestMulticlassTrainer extends MulticlassClassifierTrainer[RandomForestMulticlassClassifier]

Linear Supertypes
MulticlassClassifierTrainer[RandomForestMulticlassClassifier], BaseLinearTrainer[la.Tensor1, la.Tensor1, Int, RandomForestMulticlassClassifier], AnyRef, Any
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Inherited
  1. RandomForestMulticlassTrainer
  2. MulticlassClassifierTrainer
  3. BaseLinearTrainer
  4. AnyRef
  5. Any
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Instance Constructors

  1. new RandomForestMulticlassTrainer(numTrees: Int, numFeaturesToUse: Int, numInstancesToSample: Int, maxDepth: Int = 25, useParallel: Boolean = true, numThreads: Int = ..., treeTrainer: DecisionTreeTrainer = new ID3DecisionTreeTrainer())(implicit random: Random)

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. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def baseTrain(classifier: RandomForestMulticlassClassifier, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): Unit

    Estimate the parameters of a classifier that has already been created.

    Estimate the parameters of a classifier that has already been created.

    Definition Classes
    RandomForestMulticlassTrainer → BaseLinearTrainer

  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 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. def newModel(featureSize: Int, labelSize: Int): RandomForestMulticlassClassifier

    Definition Classes
    RandomForestMulticlassTrainer → BaseLinearTrainer

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. final def simpleTrain(labelSize: Int, featureSize: Int, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): RandomForestMulticlassClassifier

    Create a Classifier and estimate its parameters.

    Create a Classifier and estimate its parameters.

    Definition Classes
    BaseLinearTrainer

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

    Definition Classes
    AnyRef

  21. def toString(): String

    Definition Classes
    AnyRef → Any

  22. def train[Label <: LabeledDiscreteVar](classifier: RandomForestMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): Unit

    Definition Classes
    MulticlassClassifierTrainer

  23. def train[Label <: LabeledDiscreteVar](classifier: RandomForestMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): Unit

    Definition Classes
    MulticlassClassifierTrainer

  24. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes
    MulticlassClassifierTrainer

  25. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes
    MulticlassClassifierTrainer

  26. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  27. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  28. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  29. def train(classifier: RandomForestMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  30. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  31. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  32. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  33. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (RandomForestMulticlassClassifier) ⇒ Unit): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  34. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  35. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  36. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  37. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): RandomForestMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  38. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MulticlassClassifierTrainer[RandomForestMulticlassClassifier]

Inherited from BaseLinearTrainer[la.Tensor1, la.Tensor1, Int, RandomForestMulticlassClassifier]

Inherited from AnyRef

Inherited from Any

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