cc.factorie.app.classify.backend

DecisionTreeTrainer

trait DecisionTreeTrainer extends AnyRef

Self Type
DecisionTreeTrainer with DTreeBucketStats
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Known Subclasses
C45DecisionTreeTrainer, CARTDecisionTreeTrainer, DecisionStumpTrainer, ID3DecisionTreeTrainer, RegressionTreeTrainer
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Type Members

  1. abstract type State

Abstract Value Members

  1. abstract def +=(left: (DecisionTreeTrainer.this)#BucketStats, right: (DecisionTreeTrainer.this)#BucketStats): Unit

  2. abstract def -=(left: (DecisionTreeTrainer.this)#BucketStats, right: (DecisionTreeTrainer.this)#BucketStats): Unit

  3. abstract def accumulate(stats: (DecisionTreeTrainer.this)#BucketStats, inst: (DecisionTreeTrainer.this)#Instance): Unit

  4. abstract def evaluateSplittingCriteria(s: (DecisionTreeTrainer.this)#State, withStats: (DecisionTreeTrainer.this)#BucketStats, withoutStats: (DecisionTreeTrainer.this)#BucketStats): Double

  5. abstract def getBucketState(labels: Iterable[(DecisionTreeTrainer.this)#Instance]): (DecisionTreeTrainer.this)#State

  6. abstract def getBucketStats(labels: Iterable[(DecisionTreeTrainer.this)#Instance]): (DecisionTreeTrainer.this)#BucketStats

  7. abstract def getEmptyBucketStats(inst: (DecisionTreeTrainer.this)#Instance): (DecisionTreeTrainer.this)#BucketStats

  8. abstract def getPrediction(stats: (DecisionTreeTrainer.this)#BucketStats): (DecisionTreeTrainer.this)#Label

  9. abstract def makeLeaf(stats: (DecisionTreeTrainer.this)#BucketStats): DTree

  10. abstract def prune(tree: DTree, pruningSet: Seq[(DecisionTreeTrainer.this)#Instance]): DTree

  11. abstract def samePred(labels: Seq[(DecisionTreeTrainer.this)#Label]): Boolean

Concrete Value Members

  1. final def !=(arg0: AnyRef): Boolean

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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def evaluateSplittingCriteria(instances: Seq[(DecisionTreeTrainer.this)#Instance], possibleFeatureThresholds: HashMap[Int, Array[Double]]): HashMap[Int, Array[Double]]

  11. def finalize(): Unit

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  12. def getBucketPrediction(labels: Seq[(DecisionTreeTrainer.this)#Instance]): (DecisionTreeTrainer.this)#Label

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

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  14. def hasFeature(featureIdx: Int, feats: la.Tensor1, threshold: Double): Boolean

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    @inline()

  15. def hashCode(): Int

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  16. final def isInstanceOf[T0]: Boolean

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  17. var maxDepth: Int

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

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. def shouldStop(stats: Seq[(DecisionTreeTrainer.this)#Instance], depth: Int): Boolean

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

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  23. def toString(): String

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  24. def train(trainInstances: Seq[(DecisionTreeTrainer.this)#Instance], pruneInstances: Seq[(DecisionTreeTrainer.this)#Instance] = Nil, numFeaturesToUse: Int = 1)(implicit rng: Random): DTree

  25. final def wait(): Unit

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

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

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