/usr/share/octave/packages/statistics-1.3.0/@cvpartition/repartition.m is in octave-statistics 1.3.0-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | ## Copyright (C) 2014 Nir Krakauer
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn{Function File}{@var{Cnew} =} repartition (@var{C})
## Return a new cvpartition object.
##
## @var{C} should be a cvpartition object. @var{Cnew} will use the same partition_type as @var{C} but redo any randomization performed (currently, only the HoldOut type uses randomization).
##
## @seealso{cvpartition}
## @end deftypefn
## Author: Nir Krakauer
function Cnew = repartition (C)
if (nargin < 1 || nargin > 2)
print_usage ();
endif
Cnew = C;
switch C.Type
case 'kfold'
case 'given'
case 'holdout' #currently, only the HoldOut method uses randomization
n = C.NumObservations;
k = C.TestSize;
n_classes = C.n_classes;
if k < 1
f = k; #target fraction to sample
k = round (k * n); #number of samples
else
f = k / n;
endif
inds = zeros (n, 1, "logical");
if n_classes == 1
inds(randsample(n, k)) = true; #indices for test set
else #sample from each class
j = C.classes; #integer class labels
n_per_class = accumarray (j, 1);
n_classes = numel (n_per_class);
k_check = 0;
for i = 1:n_classes
ki = round(f*n_per_class(i));
inds(find(j == i)(randsample(n_per_class(i), ki))) = true;
k_check += ki;
endfor
if k_check < k #add random elements to test set to make it k
inds(find(!inds)(randsample(n - k_check, k - k_check))) = true;
elseif k_check > k #remove random elements from test set
inds(find(inds)(randsample(k_check, k_check - k))) = false;
endif
endif
Cnew.inds = inds;
case 'leaveout'
case 'resubstitution'
endswitch
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