com.cra.figaro.algorithm.decision

DecisionPolicyNN

class DecisionPolicyNN[T, U] extends DecisionPolicy[T, U]

A nearest neighbor decision policy. This policy computes an approximate decision from a sampling algorithm. The input to the class is an index (which holds (parent, decision) samples) a function that will combine a set of (decision, utility) samples into a single decision, and numNNSamples, the number of samples to use in a nearest neighbor algorithm. By default, this uses a VP-tree to store the samples.

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DecisionPolicy[T, U], AnyRef, Any
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Instance Constructors

  1. new DecisionPolicyNN(D: Index[T, U], combineFcn: (List[(Double, U, DecisionSample)]) ⇒ (U, Double), numNNSamples: Double)(implicit arg0: (T) ⇒ Distance[T])

Value Members

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def getNumNNSamples: Int

    Returns the number of nearest neighbors to use.

    Returns the number of nearest neighbors to use. If kNN is greater than 1, then return kNN. If kNN is less than 1, then return kNN* Number of Samples

  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. var numNNSamples: Double

    Attributes
    protected

  19. def setNumNNSamples(i: Double): Unit

    Set the number of nearest neighbor samples to use in policies based on nearest neighbor.

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

    Definition Classes
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  21. def toFcn(): (T) ⇒ Element[U]

    The function that returns a decision (Element[U]) given the value of the parent T

    The function that returns a decision (Element[U]) given the value of the parent T

    Definition Classes
    DecisionPolicyNN → DecisionPolicy

  22. def toString(): String

    Definition Classes
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  23. def toUtility(): (T) ⇒ Element[Double]

    The function that returns the expected utility (Element[Double]) given the value of the parent T

    The function that returns the expected utility (Element[Double]) given the value of the parent T

    Definition Classes
    DecisionPolicyNN → DecisionPolicy

  24. final def wait(): Unit

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

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

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Inherited from DecisionPolicy[T, U]

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