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.

mlpack-4.3.0                                     19 January 2024                               mlpack_fastmks(1)