NaiveBayes

Value Members

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

   Definition Classes

   AnyRef

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

   Definition Classes

   Any

3. final def ##(): Int

   Definition Classes

   AnyRef → Any

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

   Definition Classes

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

   Definition Classes

   Any

6. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

7. def baseTrain(classifier: LinearMulticlassClassifier, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

   Estimate the parameters of a classifier that has already been created.

   Estimate the parameters of a classifier that has already been created.

   Definition Classes

   NaiveBayes → BaseLinearTrainer

8. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

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   Annotations

   @throws( ... )

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

   Definition Classes

   AnyRef

10. def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

11. var evidenceSmoothingMass: Double

12. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

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    Annotations

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

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

    Definition Classes

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14. def hashCode(): Int

    Definition Classes

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15. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

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

    Definition Classes

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17. def newModel(featureSize: Int, labelSize: Int): LinearMulticlassClassifier

    Definition Classes

    NaiveBayes → BaseLinearTrainer

18. final def notify(): Unit

    Definition Classes

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19. final def notifyAll(): Unit

    Definition Classes

    AnyRef

20. final def simpleTrain(labelSize: Int, featureSize: Int, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Create a Classifier and estimate its parameters.

    Create a Classifier and estimate its parameters.

    Definition Classes

    BaseLinearTrainer

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

    Definition Classes

    AnyRef

22. def toString(): String

    Definition Classes

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23. def train[Label <: LabeledDiscreteVar](classifier: LinearMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): Unit

    Definition Classes

    MulticlassClassifierTrainer

24. def train[Label <: LabeledDiscreteVar](classifier: LinearMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): Unit

    Definition Classes

    MulticlassClassifierTrainer

25. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes

    MulticlassClassifierTrainer

26. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes

    MulticlassClassifierTrainer

27. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): Unit

    Definition Classes

    MulticlassClassifierTrainer

28. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): Unit

    Definition Classes

    MulticlassClassifierTrainer

29. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes

    MulticlassClassifierTrainer

30. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes

    MulticlassClassifierTrainer

31. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

32. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

33. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

34. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

35. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

36. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

37. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

38. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): LinearMulticlassClassifier

    Definition Classes

    MulticlassClassifierTrainer

39. final def wait(): Unit

    Definition Classes

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    Annotations

    @throws( ... )

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

    Definition Classes

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    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )