class
VPIndex[T, U] extends Index[T, U]
Instance Constructors
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new
VPIndex(stratMap: Map[(T, U), DecisionSample], capacity: Int)(implicit arg0: (T) ⇒ Distance[T])
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
getNN(parent: T, num: Int): List[(Double, U, DecisionSample)]
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def
getNNDebug(parent: T, num: Int): Iterable[(Double, Set[(U, DecisionSample)])]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
size: Int
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from Index[T, U]
Inherited from AnyRef
Inherited from Any
A VP index to compute nearest neighbor queries. This is the metric space equivalent of a k-d tree. Given a query value the index performs a best first search through the index until the guaranteed k nearest neighbors are found. See Foundations of Multidimensional and Metric Data Structures by Hanan Samet for more details
The type of the parent
The type of the decision