NAME

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

SYNOPSIS

        mlpack_lsh [-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 the file 'neighbors.csv':

       $ lsh -k 5 -r input.csv -d distances.csv -n neighbors.csv

       The output files are organized such that row i and column j in the neighbors output file  corresponds  to
       the  index  of  the  point  in the reference set which is the i'th nearest neighbor from the point in the
       query set with index j.  Row i and column j 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 option can be specified to set the random seed.

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)
              Default help info.

       --info [string]
              Get help on a specific module or option.  Default value ''.  --input_model_file (-m) [string] File
              to load LSH model from. (Cannot be specified with --reference_file.) Default value ’'.

       --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) [string]
              File containing query points (optional).  Default value ''.  --reference_file (-r)  [string]  File
              containing the reference dataset. Default value ''.  --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) [string] File
              of true neighbors to compute recall with (the recall is printed when -v  is  specified).   Default
              value ''.

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

       --version (-V)
              Display the version of mlpack.

OPTIONAL OUTPUT OPTIONS

       --distances_file  (-d)  [string]  File to output distances into. Default value ’'.  --neighbors_file (-n)
       [string] File to output neighbors into. Default value ’'.  --output_model_file (-M) [string] File to save
       LSH model to. Default value ''.

ADDITIONAL INFORMATION

ADDITIONAL INFORMATION

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

                                                                                    mlpack_lsh(16 November 2017)