NAME

       v.kcv  - Randomly partition points into test/train sets.

KEYWORDS

       vector, statistics, points, point pattern

SYNOPSIS

       v.kcv
       v.kcv --help
       v.kcv  map=name   [layer=string]   npartitions=integer   [column=name]   [--help]  [--verbose]  [--quiet]
       [--ui]

   Flags:
       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       map=name [required]
           Name of vector map
           Or data source for direct OGR access

       layer=string
           Layer number or name
           Vector features can have category values in different layers. This number determines which  layer  to
           use. When used with direct OGR access this is the layer name.
           Default: 1

       npartitions=integer [required]
           Number of partitions
           Must be > 1

       column=name
           Name for new column to which partition number is written
           Default: part

DESCRIPTION

       v.kcv  randomly  divides  a  points  lists  into  k  sets  of test/train data (for npartitions-fold cross
       validation).  Test partitions are mutually exclusive. That is, a point  will  appear  in  only  one  test
       partition  and  k-1  training  partitions.  The module generates a random point using the selected random
       number generator and then finds the closest point to it. This site is removed  from  the  candidate  list
       (meaning that it will not be selected for any other test set) and saved in the first test partition file.
       This is repeated until enough points have been selected for the test partition.   The  number  of  points
       chosen for test partitions depends upon the number of sites available and the number of partitions chosen
       (this number is made as consistent as possible while ensuring that all sites will be chosen for testing).
       This process of filling up a test partition is done k times.

NOTES

       An  ideal  random  sites  generator  will follow a Poisson distribution and will only be as random as the
       original sites. This module simply divides vector points up in a random manner.

       Be warned that random number generation occurs over the intervals defined by the current  region  of  the
       map.

       This program may not work properly with Lat-long data.

EXAMPLES

       All examples are based on the North Carolina sample dataset.
       g.copy vect=geonames_wake,my_geonames_wake
       v.kcv map=my_geonames_wake column=part npartitions=10

       g.copy vect=geodetic_pts,my_geodetic_pts
       v.kcv map=my_geodetic_pts column=part npartitions=10

SEE ALSO

        v.random, g.region

AUTHOR

       James Darrell McCauley,
       when he was at: Agricultural Engineering Purdue University

       27 Jan 1994: fixed RAND_MAX for Solaris 2.3
       13 Sep 2000: released under GPL
       Updated to 5.7 Radim Blazek 10 / 2004
       OGR support by Martin Landa (2009)
       Speed-up by Jan Vandrol and Jan Ruzicka (2013)

SOURCE CODE

       Available at: v.kcv source code (history)

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       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual