NAME

       mlpack_lsh - k-approximate-nearest-neighbor search with lsh

SYNOPSIS

        mlpack_lsh [-B int] [-H double] [-m unknown] [-k int] [-T int] [-K int] [-q unknown] [-r unknown] [-S int] [-s int] [-L int] [-t unknown] [-V bool] [-d unknown] [-n unknown] [-M unknown] [-h -v]

DESCRIPTION

       This  program  will  calculate  the  k  approximate-nearest-neighbors  of a set of points using locality-
       sensitive hashing. You may specify a separate set of  reference  points  and  query  points,  or  just  a
       reference set which will be used as both the reference and query set.

       For  example, the following will return 5 neighbors from the data for each point in 'input.csv' and store
       the distances in 'distances.csv' and the neighbors in 'neighbors.csv':

       $  mlpack_lsh  --k  5  --reference_file   input.csv   --distances_file   distances.csv   --neighbors_file
       neighbors.csv

       The  output is organized such that row i and column j in the neighbors output corresponds to the index of
       the point in the reference set which is the j'th nearest neighbor from the point in the  query  set  with
       index  i.  Row  j and column i in the distances output file corresponds to the distance between those two
       points.

       Because this is approximate-nearest-neighbors search, results may be different from run to run. Thus, the
       '--seed (-s)' parameter can be specified to set the random seed.

       This program also has many other parameters to control  its  functionality;  see  the  parameter-specific
       documentation for more information.

OPTIONAL INPUT OPTIONS

       --bucket_size (-B) [int]
              The size of a bucket in the second level hash.  Default value 500.

       --hash_width (-H) [double]
              The  hash  width  for  the first-level hashing in the LSH preprocessing. By default, the LSH class
              automatically estimates a hash width for its use. Default value 0.

       --help (-h) [bool]
              Default help info.

       --info [string]
              Print help on a specific option. Default value ''.

       --input_model_file (-m) [unknown]
              Input LSH model.

       --k (-k) [int]
              Number of nearest neighbors to find. Default value 0.

       --num_probes (-T) [int]
              Number of additional probes for multiprobe LSH; if 0, traditional LSH is used. Default value 0.

       --projections (-K) [int]
              The number of hash functions for each table  Default value 10.

       --query_file (-q) [unknown]
              Matrix containing query points (optional).

       --reference_file (-r) [unknown]
              Matrix containing the reference dataset.

       --second_hash_size (-S) [int]
              The size of the second level hash table.  Default value 99901.

       --seed (-s) [int]
              Random seed. If 0, 'std::time(NULL)' is used.  Default value 0.

       --tables (-L) [int]
              The number of hash tables to be used. Default value 30.

       --true_neighbors_file (-t) [unknown]
              Matrix of true neighbors to compute recall with (the recall is printed when -v is specified).

       --verbose (-v) [bool]
              Display informational messages and the full list of parameters and timers at the end of execution.

       --version (-V) [bool]
              Display the version of mlpack.

OPTIONAL OUTPUT OPTIONS

       --distances_file (-d) [unknown]
              Matrix to output distances into.

       --neighbors_file (-n) [unknown]
              Matrix to output neighbors into.

       --output_model_file (-M) [unknown]
              Output for trained LSH model.

ADDITIONAL INFORMATION

       For further information, including relevant papers, citations,  and  theory,  consult  the  documentation
       found at http://www.mlpack.org or included with your distribution of mlpack.

mlpack-4.6.0                                      06 April 2025                                    mlpack_lsh(1)