case class MultiTaskSplitter(randomizePivotLocation: Boolean = false, rng: Random = Random) extends Splitter[Array[AnyVal]] with Product with Serializable
Created by maxhutch on 11/29/16.
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- MultiTaskSplitter
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Instance Constructors
- new MultiTaskSplitter(randomizePivotLocation: Boolean = false, rng: Random = Random)
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- 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]
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- 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
- 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
- minInstances
the minimum number of data points on a split node
- returns
a split object that optimally divides data
- Definition Classes
- MultiTaskSplitter → Splitter
- final def getClass(): Class[_ <: AnyRef]
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- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val randomizePivotLocation: Boolean
- val rng: Random
- final def synchronized[T0](arg0: => T0): T0
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