org.apache.spark.streamdm.classifiers

SGDLearner

class SGDLearner extends Classifier

The SGDLearner trains a LinearModel using the stochastic gradient descent algorithm. The type of loss function, the lambda learning reate parameter, and the number of features need to be specified in the associated Task configuration file.

It uses the following options:

Linear Supertypes
Classifier, Learner, Serializable, Configurable, Serializable, AnyRef, Any
Known Subclasses
PerceptronLearner
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. SGDLearner
  2. Classifier
  3. Learner
  4. Serializable
  5. Configurable
  6. Serializable
  7. AnyRef
  8. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new SGDLearner()

Type Members

  1. type T = LinearModel

    Definition Classes
    SGDLearner → 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: 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
    SGDLearner → 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
    SGDLearner → Learner

  16. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  17. val lambdaOption: FloatOption

  18. val loss: Loss

  19. val lossFunctionOption: ClassOption

  20. var model: LinearModel

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

    Definition Classes
    AnyRef

  22. final def notify(): Unit

    Definition Classes
    AnyRef

  23. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  24. val numFeaturesOption: IntOption

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

    Definition Classes
    SGDLearner → Classifier

  26. val regularizer: Regularizer

  27. val regularizerOption: ClassOption

  28. val regularizerParameter: FloatOption

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

    Definition Classes
    AnyRef

  30. def toString(): String

    Definition Classes
    AnyRef → Any

  31. 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
    SGDLearner → Learner

  32. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  34. 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