NaiveBayesModel

Value Members

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

   Definition Classes

   AnyRef

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

   Definition Classes

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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. def apply(features: Vector): Double

   Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

   Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

   features

   feature vector

   returns

   prediction

   Definition Classes

   ClassificationModel

7. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

8. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

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   @throws( ... )

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

   Definition Classes

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10. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

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

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

    Definition Classes

    AnyRef → Any

12. def inputSchema: StructType

    Definition Classes

    ProbabilisticClassificationModel → Model

13. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

14. val modelType: ModelType

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

    Definition Classes

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16. final def notify(): Unit

    Definition Classes

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17. final def notifyAll(): Unit

    Definition Classes

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18. val numClasses: Int

    number of labels or labels to classify predictions into

    number of labels or labels to classify predictions into

    Definition Classes

    NaiveBayesModel → ProbabilisticClassificationModel

19. val numFeatures: Int

    number of features in feature vector

    number of features in feature vector

    Definition Classes

    NaiveBayesModel → ProbabilisticClassificationModel

20. def outputSchema: StructType

    Definition Classes

    ProbabilisticClassificationModel → Model

21. val pi: Vector

    log of class priors

22. def predict(features: Vector): Double

    Predict class based on feature vector.

    Predict class based on feature vector.

    features

    feature vector

    returns

    predicted class or probability

    Definition Classes

    ProbabilisticClassificationModel → ClassificationModel

23. def predictProbabilities(features: Vector): Vector

    Definition Classes

    ProbabilisticClassificationModel

24. def predictRaw(raw: Vector): Vector

    Definition Classes

    NaiveBayesModel → ProbabilisticClassificationModel

25. def predictWithProbability(features: Vector): (Double, Double)

    Definition Classes

    ProbabilisticClassificationModel

26. def probabilityToPrediction(probability: Vector): Double

    Definition Classes

    ProbabilisticClassificationModel

27. def probabilityToPredictionIndex(probability: Vector): Int

    Definition Classes

    ProbabilisticClassificationModel

28. def rawToPrediction(raw: Vector): Double

    Definition Classes

    ProbabilisticClassificationModel

29. def rawToProbability(raw: Vector): Vector

    Definition Classes

    ProbabilisticClassificationModel

30. def rawToProbabilityInPlace(raw: Vector): Vector

    Definition Classes

    NaiveBayesModel → ProbabilisticClassificationModel

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

    Definition Classes

    AnyRef

32. val theta: Matrix

    log of class conditional probabilities

33. def thresholds: Option[Array[Double]]

    Definition Classes

    ProbabilisticClassificationModel

34. final def wait(): Unit

    Definition Classes

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    @throws( ... )

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

    Definition Classes

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    @throws( ... )

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

    Definition Classes

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    @throws( ... )