Uses of Interface
moa.classifiers.lazy.neighboursearch.DistanceFunction
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Packages that use DistanceFunction Package Description moa.classifiers.lazy.neighboursearch -
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Uses of DistanceFunction in moa.classifiers.lazy.neighboursearch
Classes in moa.classifiers.lazy.neighboursearch that implement DistanceFunction Modifier and Type Class Description class
EuclideanDistance
Implementing Euclidean distance (or similarity) function.
One object defines not one distance but the data model in which the distances between objects of that data model can be computed.
Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.
For more information, see:
Wikipedia.class
NormalizableDistance
Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.Fields in moa.classifiers.lazy.neighboursearch declared as DistanceFunction Modifier and Type Field Description protected DistanceFunction
NearestNeighbourSearch. m_DistanceFunction
the distance function used.Methods in moa.classifiers.lazy.neighboursearch that return DistanceFunction Modifier and Type Method Description DistanceFunction
KDTree. getDistanceFunction()
returns the distance function currently in use.DistanceFunction
NearestNeighbourSearch. getDistanceFunction()
returns the distance function currently in use.Methods in moa.classifiers.lazy.neighboursearch with parameters of type DistanceFunction Modifier and Type Method Description void
KDTree. setDistanceFunction(DistanceFunction df)
sets the distance function to use for nearest neighbour search.void
NearestNeighbourSearch. setDistanceFunction(DistanceFunction df)
sets the distance function to use for nearest neighbour search.
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