NAME

       mlpack_fastmks - fastmks (fast max-kernel search)

SYNOPSIS

        mlpack_fastmks [-w double] [-b double] [-d double] [-m unknown] [-k int] [-K string] [-N bool] [-o double] [-q unknown] [-r unknown] [-s double] [-S bool] [-V bool] [-i unknown] [-p unknown] [-M unknown] [-h -v]

DESCRIPTION

       This  program  will find the k maximum kernels 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 with the '--kernel (-K)' parameter.

       For example, the following command will  calculate,  for  each  point  in  the  query  set
       'query.csv',  the  five  points  in  the reference set 'reference.csv' with maximum kernel
       evaluation using the  linear  kernel.  The  kernel  evaluations  may  be  saved  with  the
       'kernels.csv'  output parameter and the indices may be saved with the 'indices.csv' output
       parameter.

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

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

       This program performs FastMKS using a cover tree. The base used to build  the  cover  tree
       can be specified with the '--base (-b)' parameter.

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) [bool]
              Default help info.

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

       --input_model_file (-m) [unknown]
              Input FastMKS model to use.

       --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) [bool]
              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) [unknown]
              The query dataset.

       --reference_file (-r) [unknown]
              The reference dataset.

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

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

       --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

       --indices_file (-i) [unknown]
              Output matrix of indices.

       --kernels_file (-p) [unknown]
              Output matrix of kernels.

       --output_model_file (-M) [unknown]
              Output for FastMKS 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.