
@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 ManhattanHashFunctionFamily 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  | 
ManhattanHashFunctionFamily.Parameterizer
Parameterization class. 
 | 
k, proj, random, width| Constructor and Description | 
|---|
ManhattanHashFunctionFamily(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, getInputTypeRestrictionpublic ManhattanHashFunctionFamily(RandomFactory random, double width, int k)
random - Random generatorwidth - Bin widthk - Number of projections to combine.public boolean isCompatible(DistanceFunction<?,?> df)
LocalitySensitiveHashFunctionFamilydf - Distance function.true when appropriate.