NAME

       mlpack_fastmks - fastmks (fast max-kernel search)

SYNOPSIS

        mlpack_fastmks [-h] [-v]

DESCRIPTION

       This  program  will  find the k maximum kernel of a set of points, using a query set and a
       reference set (which can optionally be the same set). More specifically, for each point in
       the  query  set,  the  k  points  in the reference set with maximum kernel evaluations are
       found. The kernel function used is specified by --kernel.

       For example, the following command will calculate, for each point in ’query.csv', the five
       points  in  'reference.csv'  with  maximum  kernel evaluation using the linear kernel. The
       kernel  evaluations  are  stored  in  'kernels.csv'  and  the  indices   are   stored   in
       'indices.csv'.

       $  fastmks  --k  5  --reference_file  reference.csv  --query_file query.csv --indices_file
       indices.csv --kernels_file kernels.csv --kernel linear

       The output files are organized such that row i and column j in  the  indices  output  file
       corresponds  to  the  index of the point in the reference set that has i'th largest kernel
       evaluation with the point in the query set with index j. Row i and column j in the kernels
       output file corresponds to the kernel evaluation between those two points.

       This executable performs FastMKS using a cover tree. The base used to build the cover tree
       can be specified with the --base option.

OPTIONAL INPUT OPTIONS

       --bandwidth (-w) [double]
              Bandwidth (for Gaussian, Epanechnikov, and triangular kernels). Default value 1.

       --base (-b) [double]
              Base to use during cover tree construction.  Default value 2.

       --degree (-d) [double]
              Degree of polynomial kernel. Default value 2.

       --help (-h)
              Default help info.

       --info [string]
              Get help on a specific module or option.   Default  value  ''.   --input_model_file
              (-m) [string] File containing FastMKS model. Default value ’'.

       --k (-k) [int]
              Number of maximum kernels to find. Default value 0.

       --kernel (-K) [string]
              Kernel  type  to use: 'linear', 'polynomial', ’cosine', 'gaussian', 'epanechnikov',
              ’triangular', 'hyptan'. Default value ’linear'.

       --naive (-N)
              If true, O(n^2) naive mode is used for computation.

       --offset (-o) [double]
              Offset of kernel (for polynomial and hyptan kernels). Default value 0.

       --query_file (-q) [string]
              File containing  the  query  dataset.  Default  value  ''.   --reference_file  (-r)
              [string] File containing the reference dataset. Default value ''.

       --scale (-s) [double]
              Scale of kernel (for hyptan kernel). Default value 1.

       --single (-S)
              If true, single-tree search is used (as opposed to dual-tree search.

       --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

       --indices_file (-i) [string] File to save indices  of  kernels  into.  Default  value  ''.
       --kernels_file   (-p)   [string]   File   to   save   kernels   into.  Default  value  ''.
       --output_model_file (-M) [string] File to save FastMKS 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_fastmks(16 November 2017)