org.apache.spark.streamdm.classifiers.bayes

MultinomialNaiveBayes

class MultinomialNaiveBayes extends Classifier

Incremental Multinomial Naive Bayes learner. Builds a bayesian text classifier making the naive assumption that all inputs are independent and that feature values represent the frequencies with words occur. For more information see,

Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.

It uses the following options:

Linear Supertypes
Classifier, Learner, Serializable, Configurable, Serializable, AnyRef, Any
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Inherited
  1. MultinomialNaiveBayes
  2. Classifier
  3. Learner
  4. Serializable
  5. Configurable
  6. Serializable
  7. AnyRef
  8. Any
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Instance Constructors

  1. new MultinomialNaiveBayes()

Type Members

  1. type T = MultinomialNaiveBayesModel

    Definition Classes
    MultinomialNaiveBayes → Learner

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. var exampleLearnerSpecification: ExampleSpecification

  11. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  13. def getModel: MultinomialNaiveBayesModel

    Gets the current Model used for the Learner.

    Gets the current Model used for the Learner.

    returns

    the Model object used for training

    Definition Classes
    MultinomialNaiveBayes → Learner

  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  15. def init(exampleSpecification: ExampleSpecification): Unit

    Init the model based on the algorithm implemented in the learner.

    Init the model based on the algorithm implemented in the learner.

    exampleSpecification

    the ExampleSpecification of the input stream.

    Definition Classes
    MultinomialNaiveBayes → Learner

  16. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  17. val laplaceSmoothingFactorOption: IntOption

  18. var model: MultinomialNaiveBayesModel

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

    Definition Classes
    AnyRef

  20. final def notify(): Unit

    Definition Classes
    AnyRef

  21. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  22. val numClassesOption: IntOption

  23. val numFeaturesOption: IntOption

  24. def predict(input: DStream[Example]): DStream[(Example, Double)]

    Definition Classes
    MultinomialNaiveBayes → Classifier

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

    Definition Classes
    AnyRef

  26. def toString(): String

    Definition Classes
    AnyRef → Any

  27. def train(input: DStream[Example]): Unit

    Train the model based on the algorithm implemented in the learner, from the stream of Examples given for training.

    Train the model based on the algorithm implemented in the learner, from the stream of Examples given for training.

    input

    a stream of Examples

    Definition Classes
    MultinomialNaiveBayes → Learner

  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Classifier

Inherited from Learner

Inherited from Serializable

Inherited from Configurable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped