Class/Object

com.cra.figaro.algorithm.decision

DecisionPolicyNN

Related Docs: object DecisionPolicyNN | package decision

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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.

Linear Supertypes
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])

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Value Members

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

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  2. final def ##(): Int

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

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

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

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  10. def getNumNNSamples: Int

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    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.

  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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  16. var numNNSamples: Double

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    Attributes
    protected

  17. def setNumNNSamples(i: Double): Unit

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

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

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

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    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

  20. def toString(): String

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  21. def toUtility(): (T) ⇒ Element[Double]

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    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

  22. final def wait(): Unit

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

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

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Inherited from DecisionPolicy[T, U]

Inherited from AnyRef

Inherited from Any

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