NaiveBayesModel

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

   AnyRef

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

   Definition Classes

   Any

6. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

7. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

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

   Definition Classes

   AnyRef

9. def equals(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

10. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

11. def formatVersion: String

    Current version of model save/load format.

    Current version of model save/load format.

    Attributes

    protected

    Definition Classes

    NaiveBayesModel → Saveable

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

    Definition Classes

    AnyRef → Any

13. def hashCode(): Int

    Definition Classes

    AnyRef → Any

14. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

15. val labels: Array[Double]

    list of labels

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

    Definition Classes

    AnyRef

17. final def notify(): Unit

    Definition Classes

    AnyRef

18. final def notifyAll(): Unit

    Definition Classes

    AnyRef

19. val pi: Array[Double]

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

20. 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

21. 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

22. 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

23. def save(sc: SparkContext, path: String): Unit

    Save this model to the given path.

    Save this model to the given path.

    This saves:

    • human-readable (JSON) model metadata to path/metadata/
    • Parquet formatted data to path/data/

    The model may be loaded using Loader.load.

    sc

    Spark context used to save model data.

    path

    Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.

    Definition Classes

    NaiveBayesModel → Saveable

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

    Definition Classes

    AnyRef

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

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

26. def toString(): String

    Definition Classes

    AnyRef → Any

27. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )