org.apache.spark.streamdm.classifiers

MultiClassLearner

class MultiClassLearner extends Classifier

The MultiClassLearner trains a model for each class. The class predicted is the one that its model predicts with highest confidence.

It uses the following option:

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

  1. new MultiClassLearner()

Type Members

  1. type T = LinearModel

    Definition Classes
    MultiClassLearner → 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. val baseClassifierOption: ClassOption

  8. var classifiers: Array[Classifier]

  9. def clone(): AnyRef

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

  10. def ensemblePredict(example: Example): Double

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

    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  13. var exampleLearnerSpecification: ExampleSpecification

  14. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  16. def getModel: LinearModel

    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
    MultiClassLearner → Learner

  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  18. 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
    MultiClassLearner → Learner

  19. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  21. final def notify(): Unit

    Definition Classes
    AnyRef

  22. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

    Definition Classes
    MultiClassLearner → Classifier

  24. var sizeEnsemble: Int

  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
    MultiClassLearner → 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

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