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.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

5.  def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @native() @throws( ... )

6.  def computeImpurity(labels: Seq[(Array[AnyVal], Double)]): Double

   Compute the impurity of a set of weighted labels

   Compute the impurity of a set of weighted labels

   labels

   is a seq of (Array of multiple labels, single weight)

   returns

   the impurity, which is in [0, number of labels * sum of weights]

7.  final def eq(arg0: AnyRef): Boolean

   Definition Classes

   AnyRef

8.  def equals(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

9.  def finalize(): Unit

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

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

10.  def getBestCategoricalSplit(data: Seq[(Vector[AnyVal], Array[AnyVal], Double)], calculator: MultiImpurityCalculator, index: Int, minCount: Int): (Split, Double)

    Get find the best categorical splitter.

    Get find the best categorical splitter.

    data

    to split

    index

    of the feature to split on

    returns

    the best split of this feature

11.  def getBestRealSplit(data: Seq[(Vector[AnyVal], Array[AnyVal], Double)], calculator: MultiImpurityCalculator, index: Int, minCount: Int): (Split, Double)

    Find the best split on a continuous variable

    Find the best split on a continuous variable

    data

    to split

    index

    of the feature to split on

    returns

    the best split of this feature

12.  def getBestSplit(data: Seq[(Vector[AnyVal], Array[AnyVal], Double)], numFeatures: Int, minInstances: Int): (Split, Double)

    Get the best split, considering numFeature random features (w/o replacement)

    Get the best split, considering numFeature random features (w/o replacement)

    data

    to split

    numFeatures

    to consider, randomly

    returns

    a split object that optimally divides data

13.  final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

14.  def hashCode(): Int

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

15.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

16.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

17.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

18.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

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

    Definition Classes

    AnyRef

20.  def toString(): String

    Definition Classes

    AnyRef → Any

21.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

23.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @native() @throws( ... )