RandomForest

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 allFeatures: Set[Int]

   

   The set of all features found in at least one decision tree of the collection.

   The set of all features found in at least one decision tree of the collection.

   Definition Classes

   RandomForest → ProbabilisticClassifier

5. val allOutcomes: Seq[Int]

   

   the collection of possible outcomes

6. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

7. def classify(featureVector: FeatureVector): (Int, Option[Justification])

   

   Classifies an feature vector and optionally returns a "justification" for the classification decision.

   Classifies an feature vector and optionally returns a "justification" for the classification decision.

   featureVector

   feature vector to classify

   returns

   (predicted outcome, optional justification for the prediction)

   Definition Classes

   ProbabilisticClassifier

8. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

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   Annotations

   @throws( ... )

9. val decisionTrees: Seq[DecisionTree]

   

   the collection of decision trees

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

    

    Definition Classes

    AnyRef

11. def finalize(): Unit

    

    Attributes

    protected[java.lang]

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    @throws( classOf[java.lang.Throwable] )

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

    

    Definition Classes

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13. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

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

    

    Definition Classes

    AnyRef

15. final def notify(): Unit

    

    Definition Classes

    AnyRef

16. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

17. def outcomeDistribution(featureVector: FeatureVector): (OutcomeDistribution, Option[Justification])

    

    Each decision gets a single vote about the outcome.

    Each decision gets a single vote about the outcome. The produced distribution is the normalized histogram of the votes.

    featureVector

    feature vector to find outcome distribution for

    returns

    a probability distribution over outcomes

    Definition Classes

    RandomForest → ProbabilisticClassifier

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

    

    Definition Classes

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19. final def wait(): Unit

    

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    @throws( ... )

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

    

    Definition Classes

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    @throws( ... )

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

    

    Definition Classes

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    @throws( ... )