bionic (1) mlpack_emst.1.gz

Provided by: mlpack-bin_2.2.5-1build1_amd64 bug

NAME

       mlpack_emst - fast euclidean minimum spanning tree

SYNOPSIS

        mlpack_emst [-h] [-v]

DESCRIPTION

       This program can compute the Euclidean minimum spanning tree of a set of input points using the dual-tree
       Boruvka algorithm.

       The output is saved in a three-column matrix,  where  each  row  indicates  an  edge.  The  first  column
       corresponds  to  the  lesser index of the edge; the second column corresponds to the greater index of the
       edge; and the third column corresponds to the distance between the two points.

REQUIRED INPUT OPTIONS

       --input_file (-i) [string]
              Data input file.

OPTIONAL INPUT OPTIONS

       --help (-h)
              Default help info.

       --info [string]
              Get help on a specific module or option.  Default value ''.

       --leaf_size (-l) [int]
              Leaf size in the kd-tree. One-element leaves give the empirically best  performance,  but  at  the
              cost of greater memory requirements.  Default value 1.

       --naive (-n)
              Compute the MST using O(n^2) naive algorithm.

       --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

       --output_file (-o) [string]
              Data output file. Stored as an edge list.  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_emst(16 November 2017)