brushfire

Type Members

1. case class BinarySplitter[V, T](partition: (V) ⇒ Predicate[V])(implicit evidence$1: Ordering[V], evidence$2: Monoid[T]) extends Splitter[V, T] with Product with Serializable

   

2. case class BinnedSplitter[V, T](original: Splitter[V, T])(fn: (V) ⇒ V) extends Splitter[V, T] with Product with Serializable

   

3. type BranchLabel[K, V, A] = (K, Predicate[V], A)

   

4. case class ChiSquaredEvaluator[V, L, W]()(implicit weightMonoid: Monoid[W], weightDouble: (W) ⇒ Double) extends Evaluator[V, Map[L, W]] with Product with Serializable

   

5. trait Defaults extends LowPriorityDefaults

   

6. case class DispatchedSplitter[A, B, C, D, T](ordinal: Splitter[A, T], nominal: Splitter[B, T], continuous: Splitter[C, T], sparse: Splitter[D, T])(implicit evidence$3: Ordering[A], evidence$4: Ordering[C]) extends Splitter[Dispatched[A, B, C, D], T] with Product with Serializable

   

7. case class ErrorEvaluator[V, T, P, E](error: Error[T, P, E], voter: Voter[T, P])(fn: (E) ⇒ Double) extends Evaluator[V, T] with Product with Serializable

   

8. trait Evaluator[V, T] extends AnyRef

   

   Evaluates the goodness of a candidate split

9. case class FrequencyStopper[L](maxInMemorySize: Long, minSize: Long) extends Stopper[Map[L, Long]] with Product with Serializable

   

10. case class Instance[K, V, T](id: String, timestamp: Long, features: Map[K, V], target: T) extends Product with Serializable

    

    Represents a single instance of training data.

    Represents a single instance of training data.

    K

    feature names

    V

    feature values

    T

    target distribution

    id

    an identifier unique to this instance

    timestamp

    the time this instance was observed

    features

    a map of named features that make up this instance

    target

    a distribution of predictions or labels for this instance

11. case class KFoldSampler(numTrees: Int) extends Sampler[Any] with Product with Serializable

    

12. type LeafLabel[T, A] = (Int, T, A)

    

13. trait LowPriorityDefaults extends AnyRef

    

14. case class MinWeightEvaluator[V, L, W](minWeight: (W) ⇒ Boolean, wrapped: Evaluator[V, Map[L, W]])(implicit evidence$1: Monoid[W]) extends Evaluator[V, Map[L, W]] with Product with Serializable

    

15. case class OutOfTimeSampler[K](base: Sampler[K], threshold: Long) extends Sampler[K] with Product with Serializable

    

16. case class QTreeSplitter[T](k: Int)(implicit evidence$5: Monoid[T]) extends Splitter[Double, T] with Product with Serializable

    

17. case class RFSampler(numTrees: Int, featureRate: Double, samplingRate: Double = 1.0) extends Sampler[String] with Product with Serializable

    

18. case class RandomSplitter[V, T](original: Splitter[V, T]) extends Splitter[V, T] with Product with Serializable

    

19. trait Sampler[-K] extends AnyRef

    

    Allocates instances and features to trees and training or validation sets

20. case class SpaceSaverSplitter[V, L](capacity: Int = 1000) extends Splitter[V, Map[L, Long]] with Product with Serializable

    

21. case class Split[V, T](predicate: Predicate[V], leftDistribution: T, rightDistribution: T) extends Product with Serializable

    

    Candidate split for a tree node

22. trait Splitter[V, T] extends AnyRef

    

    Produces candidate splits from the instances at a leaf node.

    Produces candidate splits from the instances at a leaf node.

    V

    feature values

    T

    target distributions

23. trait Stopper[T] extends AnyRef

    

    Provides stopping conditions which guide when splits will be attempted

24. case class TDigestSplitter[L](k: Int = 25, compression: Double = 100.0) extends Splitter[Double, Map[L, Long]] with Product with Serializable

    

25. case class TimeGroupedSampler[K](base: Sampler[K], period: Long, groups: Int) extends Sampler[K] with Product with Serializable

    

26. type Tree[K, V, T] = AnnotatedTree[K, V, T, Unit]