Uses of Package
moa.classifiers.lazy.neighboursearch

Packages that use moa.classifiers.lazy.neighboursearch

Package	Description
moa.classifiers.lazy.neighboursearch
moa.classifiers.lazy.neighboursearch.kdtrees

Classes in moa.classifiers.lazy.neighboursearch used by moa.classifiers.lazy.neighboursearch

Class and Description
DistanceFunction Interface for any class that can compute and return distances between two instances.
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.
NearestNeighbourSearch Abstract class for nearest neighbour search.
NearestNeighbourSearch.MyHeap A class for a heap to store the nearest k neighbours to an instance.
NearestNeighbourSearch.MyHeapElement A class for storing data about a neighboring instance.
NearestNeighbourSearch.NeighborNode A class for storing data about a neighboring instance.
NormalizableDistance Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.

Classes in moa.classifiers.lazy.neighboursearch used by moa.classifiers.lazy.neighboursearch.kdtrees

Class and Description
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.