a function defining a metric over a vector space
pairs that are >= to the distance are discarded
compute for the random fraction of queries
compute for the random fraction of the catalog
Find the k nearest neighbours in catalogMatrix for each entry in queryMatrix.
Find the k nearest neighbours in catalogMatrix for each entry in queryMatrix. Implementations may be either exact or approximate.
a row oriented matrix. Each row in the matrix represents an item in the data set. Items are identified by their matrix index.
a row oriented matrix. Each row in the matrix represents an item in the data set. Items are identified by their matrix index.
a similarity matrix with MatrixEntry(queryA, catalogB, similarity).
Brute force O(size(query) * size(catalog)) method to compute exact nearest neighbours for rows in the query matrix. As this is a very expensive computation, additional sample parameters may be passed such that neighbours are just computed for a random fraction of the data set.