cosmo balance dataset hdrΒΆ

function [balanced_ds,idxs,classes]=cosmo_balance_dataset(ds,varargin)
% sub-sample a dataset to have an equal number of samples for each target
% [balanced_ds,idxs,classes]=cosmo_balance_dataset(ds)
% Inputs:
%   ds                      dataset struct with fields .samples,
%                           .sa.targets and .sa.chunks. All values in
%                           .sa.chunks must be different from each other.
%   'sample_balancer', f    (optional)
%                           function handle with signature
%                               [idxs,classes]=f(targets,seed)
%                           where idxs is a SxC vector with indices for C
%                           classes and S targets per class. If omitted a
%                           builtin function is used.
%   'seed', s               (optional, default=1)
%                           Seed to use for pseudo-random number generation
% Output:
%   balanced_ds             dataset with a subset of the samples from ds
%                           so that each target occurs equally often.
%                           Selection is (by default) done in a
%                           pseudo-determistic manner.
%   idxs                    SxC vector indicating which
%   classes                 Cx1 vector containing unique class labels
% Notes:
%   - this function is to be used with MEEG datasets. it is not intended
%     for fMRI data.
% #   For CoSMoMVPA's copyright information and license terms,   #
% #   see the COPYING file distributed with CoSMoMVPA.           #