@Reference(authors="M. Datar and N. Immorlica and P. Indyk and V. S. Mirrokni", title="Locality-sensitive hashing scheme based on p-stable distributions", booktitle="Proc. 20th annual symposium on Computational geometry", url="http://dx.doi.org/10.1145/997817.997857") public class EuclideanHashFunctionFamily extends AbstractHashFunctionFamily
Locality-sensitive hashing scheme based on p-stable distributions
M. Datar and N. Immorlica and P. Indyk and V. S. Mirrokni
Proc. 20th annual symposium on Computational geometry
Modifier and Type | Class and Description |
---|---|
static class |
EuclideanHashFunctionFamily.Parameterizer
Parameterization class.
|
k, proj, random, width
Constructor and Description |
---|
EuclideanHashFunctionFamily(RandomFactory random,
double width,
int k)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
boolean |
isCompatible(DistanceFunction<?,?> df)
Check whether the given distance function can be accelerated using this
hash family.
|
generateHashFunctions, getInputTypeRestriction
public EuclideanHashFunctionFamily(RandomFactory random, double width, int k)
random
- Random generatorwidth
- Bin widthk
- Number of projections to combine.public boolean isCompatible(DistanceFunction<?,?> df)
LocalitySensitiveHashFunctionFamily
df
- Distance function.true
when appropriate.