com.cra.figaro.algorithm.learning

ExpectationMaximization

abstract class ExpectationMaximization extends Algorithm with ParameterLearner

Base class of Expectation Maximization algorithms. This class also implements the outer EM loop and checks against termination criteria.

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Instance Constructors

  1. new ExpectationMaximization(universe: Universe, terminationCriteria: () ⇒ EMTerminationCriteria, targetParameters: Parameter[_]*)

Abstract Value Members

  1. abstract def doExpectationStep(): Map[Parameter[_], Seq[Double]]

    Attributes
    protected

Concrete Value Members

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

    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Definition Classes
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  4. var active: Boolean

    Attributes
    protected
    Definition Classes
    Algorithm
  5. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  6. def cleanUp(): Unit

    Called when the algorithm is killed.

    Called when the algorithm is killed. By default, does nothing. Can be overridden.

    Definition Classes
    Algorithm
  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. val debug: Boolean

  9. def doKill(): Unit

    Attributes
    protected
    Definition Classes
    ExpectationMaximizationAlgorithm
  10. def doMaximizationStep(parameterMapping: Map[Parameter[_], Seq[Double]]): Unit

    Attributes
    protected
  11. def doResume(): Unit

    Attributes
    protected
    Definition Classes
    ExpectationMaximizationAlgorithm
  12. def doStart(): Unit

    Attributes
    protected
    Definition Classes
    ExpectationMaximizationAlgorithm
  13. def doStop(): Unit

    Attributes
    protected
    Definition Classes
    ExpectationMaximizationAlgorithm
  14. def em(): Unit

    Attributes
    protected
  15. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  17. def finalize(): Unit

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    protected[java.lang]
    Definition Classes
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    @throws( classOf[java.lang.Throwable] )
  18. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  19. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  20. def initialize(): Unit

    Called when the algorithm is started before running any steps.

    Called when the algorithm is started before running any steps. By default, does nothing. Can be overridden.

    Definition Classes
    Algorithm
  21. def isActive: Boolean

    Definition Classes
    Algorithm
  22. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  23. def iteration(): Unit

  24. def kill(): Unit

    Kill the algorithm so that it is inactive.

    Kill the algorithm so that it is inactive. It will no longer be able to provide answers.Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  25. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  26. final def notify(): Unit

    Definition Classes
    AnyRef
  27. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  28. def resume(): Unit

    Resume the computation of the algorithm, if it has been stopped.

    Resume the computation of the algorithm, if it has been stopped. Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  29. def start(): Unit

    Start the algorithm and make it active.

    Start the algorithm and make it active. After it returns, the algorithm must be ready to provide answers. Throws AlgorithmActiveException if the algorithm is already active.

    Definition Classes
    Algorithm
  30. def stop(): Unit

    Stop the algorithm from computing.

    Stop the algorithm from computing. The algorithm is still ready to provide answers after it returns. Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  31. var sufficientStatistics: Map[Parameter[_], Seq[Double]]

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

    Definition Classes
    AnyRef
  33. val terminationCriteria: () ⇒ EMTerminationCriteria

  34. def toString(): String

    Definition Classes
    AnyRef → Any
  35. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  36. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  37. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ParameterLearner

Inherited from Algorithm

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