cosmo classify matlabsvm 2class hdrΒΆ

function predicted=cosmo_classify_matlabsvm_2class(samples_train, targets_train, samples_test, opt)
% svm classifier wrapper (around svmtrain/svmclassify)
%
% predicted=cosmo_classify_matlabsvm_2class(samples_train, targets_train, samples_test, opt)
%
% Inputs:
%   samples_train      PxR training data for P samples and R features
%   targets_train      Px1 training data classes
%   samples_test       QxR test data
%   opt                struct with options. supports any option that
%                      svmtrain supports
%
% Output:
%   predicted          Qx1 predicted data classes for samples_test
%
% Notes:
%  - this function uses Matlab's builtin svmtrain function, which has
%    the same name as LIBSVM's version. Use of this function is not
%    supported when LIBSVM's svmtrain precedes in the matlab path; in
%    that case, adjust the path or use cosmo_classify_libsvm instead.
%  - Matlab's SVM classifier is rather slow, especially for multi-class
%    data (more than two classes). When classification takes a long time,
%    consider using libsvm.
%  - for a guide on svm classification, see
%      http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf
%    Note that cosmo_crossvalidate and cosmo_crossvalidation_measure
%    provide an option 'normalization' to perform data scaling
%  - As of Matlab 2017a (maybe earlier), Matlab gives the warning that
%      'svmtrain will be removed in a future release. Use fitcsvm instead.'
%    however fitcsvm gives different results than svmtrain. In this
%    function the warning message is suppressed.
%
% See also svmtrain, svmclassify, cosmo_classify_matlabsvm
%
% #   For CoSMoMVPA's copyright information and license terms,   #
% #   see the COPYING file distributed with CoSMoMVPA.           #