Used as it is, except some version compatibility changes. lines: 3,4,12-16

psvm_classification.m

clear all;
clc;
stype={'char','pos','bar','pie'}; %modified here
load('S2.mat')  %S2.mat is the correct response data w.r.t. response_fld0.05_correct.mat
eegdata=S;
for type=1:4
%     load('processed_data\features2_normalized.mat');
%     load('processed_data\features_mRMR_400mid.mat');
%     load('processed_data\processed_target_2s1.mat');      
%     load('processed_data\features_target_final.mat');
  
    load('etc\feature_response_fld_0.05.mat')
    %% This is where I modified for version compatibility
    tp = processed_meta_2s(:,4);
    l = strcmp(tp,stype{type});
    idx = find(l);
    S=eegdata;
    %% 
    S=S(idx,:);
    nback_target=nback_target(idx,:);
    
    fprintf('Type : %s\n',stype{type});
    fprintf('Number of samples for..\n');
    fprintf('0,1,2,3 back respectively :%4d,%4d,%4d,%4d\n',size(find(nback_target==0),1),size(find(nback_target==1),1),size(find(nback_target==2),1),size(find(nback_target==3),1));
    
    fprintf('--------------------------------------------\n');
    fprintf('          Test Acc      F1 score\n');
    
    for j=0:2
        for k=(j+1):3
            
            num1=j;
            num2=k;
    
            idx1=find(nback_target==num1);
            idx2=find(nback_target==num2);
            
            data1=S(idx1,:);
            data2=S(idx2,:);
            
            A=[data1;data2];
            Y=[ones(size(idx1,1),1); -1*ones(size(idx2,1),1)];
            
            ridx=randperm(size(Y,1));
            A=A(ridx,:);
            Y=Y(ridx,:);
            
            
            [w gamma train test trainf1 testf1 time nu]=psvm(A,Y,10,0,false,1);
            
            % [w gamma train test time nu] = n_psvm(A,Y,0.5,5);
            fprintf('%d vs %d %10.2f %10.2f\n',num1,num2,test,testf1);
        end
    end
    fprintf('--------------------------------------------\n');
end