Package moa.classifiers.lazy.neighboursearch

Interface Summary

Interface	Description
DistanceFunction	Interface for any class that can compute and return distances between two instances.

Class Summary

Class	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.
KDTree	Class implementing the KDTree search algorithm for nearest neighbour search. The connection to dataset is only a reference.
LinearNNSearch	Class implementing the brute force search algorithm for nearest neighbour search.
NearestNeighbourSearch	Abstract class for nearest neighbour search.
NormalizableDistance	Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.