NaiveBayesModel

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

   

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2. final def ##(): Int

   

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

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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

   

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10. def hashCode(): Int

    

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11. final def isInstanceOf[T0]: Boolean

    

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12. val labels: Array[Double]

    

    list of labels

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

    

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14. final def notify(): Unit

    

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15. final def notifyAll(): Unit

    

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16. val pi: Array[Double]

    

    log of class priors, whose dimension is C, number of labels

17. def predict(testData: Vector): Double

    

    Predict values for a single data point using the model trained.

    Predict values for a single data point using the model trained.

    testData

    array representing a single data point

    returns

    predicted category from the trained model

    Definition Classes

    NaiveBayesModel → ClassificationModel

18. def predict(testData: RDD[Vector]): RDD[Double]

    

    Predict values for the given data set using the model trained.

    Predict values for the given data set using the model trained.

    testData

    RDD representing data points to be predicted

    returns

    an RDD[Double] where each entry contains the corresponding prediction

    Definition Classes

    NaiveBayesModel → ClassificationModel

19. def predict(testData: JavaRDD[Vector]): JavaRDD[Double]

    

    Predict values for examples stored in a JavaRDD.

    Predict values for examples stored in a JavaRDD.

    testData

    JavaRDD representing data points to be predicted

    returns

    a JavaRDD[java.lang.Double] where each entry contains the corresponding prediction

    Definition Classes

    ClassificationModel

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

    

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21. val theta: Array[Array[Double]]

    

    log of class conditional probabilities, whose dimension is C-by-D, where D is number of features

22. def toString(): String

    

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23. final def wait(): Unit

    

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

    

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

    

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