Calculates the distance between 2 vectors
K-nearest neighbors search index.
K-nearest neighbors search index.
Type of the external identifier of an item
Type of the vector to perform distance calculation on
Type of items stored in the index
Type of distance between items (expect any numeric type: float, double, int, ..).
See https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm for more information.
Item that can be indexed
Serializes objects
Called periodically to report on progress during indexing.
Called periodically to report on progress during indexing. The first argument is the number of records processed. The second argument is the total number of record to index as part of this operation.
Result of a nearest neighbour search.
A sparse vector represented by an index array and a value array.
Calculates the bray curtis distance.
Calculates the canberra distance.
Calculates the bray correlation distance.
Calculates the cosine distance.
Calculates the euclidean distance.
Calculates the inner product.
Calculates the manhattan distance.
Calculates the inner product.
Calculates the bray curtis distance.
Calculates the canberra distance.
Calculates the correlation distance.
Calculates the cosine distance.
Calculates the euclidean distance.
Calculates the inner product.
Calculates the manhattan distance.
Calculates the inner product.