Dawn@4: function [] = SVM_HNR_Singing(  inputFileName )
Dawn@4: 
Dawn@4: cd 'C:\Users\dawn\Dropbox\TestResults'
Dawn@4: 
Dawn@4: DEBUG = 1;
Dawn@4: % output results file name
Dawn@4: % masterFileOutputID = fopen( 'SVM_Singing_HNR.txt', 'a' );
Dawn@4: outputFileName = ['SVM_' inputFileName];
Dawn@4: masterFileOutputID = fopen( outputFileName, 'a' );
Dawn@4: 
Dawn@4: % input results file name
Dawn@4: % inputFileName = 'singingBasicHNRStats.txt';
Dawn@4: 
Dawn@4: % fprintf( masterFileOutputID, '\n RESULTS FILE NAME: %s\n', inputFileName);
Dawn@4: inputFileID = fopen( inputFileName );
Dawn@4: 
Dawn@4: % noOfArguments = length(varargin);
Dawn@4: 
Dawn@4: % outputFileName = 'individualResults/SVM_Results_';
Dawn@4: % resultsFileName = 'SVM_Results_';
Dawn@4: % titleName = '';
Dawn@4: % for i=1 : noOfArguments
Dawn@4: %     titleName = [ titleName varargin{i} '_'];
Dawn@4: %     fprintf( masterFileOutputID, '%s_', varargin{i} );
Dawn@4: % end
Dawn@4: 
Dawn@4: % outputFileName = [ outputFileName titleName ];
Dawn@4: % resultsFileName = [ resultsFileName titleName ];
Dawn@4: 
Dawn@4: fprintf( masterFileOutputID, '\t' );
Dawn@4: 
Dawn@4: % outputFileName = [ outputFileName '.txt'];
Dawn@4: % resultsFileName = [ resultsFileName '.txt'];
Dawn@4: % 
Dawn@4: % fileOutputID = fopen( outputFileName, 'w' );
Dawn@4: % fileSVMOutputID = fopen( resultsFileName, 'w' );
Dawn@4: 
Dawn@4: % -------------------- get the data from the results file ---------------
Dawn@4: lineCount = 0;
Dawn@4: fileCount = 0;
Dawn@4: data = [];
Dawn@4: groups = [];
Dawn@4: 
Dawn@4: while( ~(feof(inputFileID)) )
Dawn@4:     
Dawn@4:     outputValues = [];
Dawn@4:     thestr = fgetl(inputFileID);
Dawn@4:     fileCount = fileCount + 1;
Dawn@4: 
Dawn@4:     % determine whether we have a positive or negative sample
Dawn@4:     sampleEmotion( fileCount ) = 'U';
Dawn@4:     if( ~(isempty(strfind(thestr,'pos'))))
Dawn@4:         % sample is positive
Dawn@4:         sampleEmotion( fileCount ) = 'P';
Dawn@4:         groups( fileCount ) = 1;
Dawn@4:     elseif( ~(isempty(strfind(thestr,'neg'))))
Dawn@4:         % sample is negative
Dawn@4:         sampleEmotion( fileCount ) = 'N';
Dawn@4:         groups( fileCount ) = 0;
Dawn@4:     else
Dawn@4:         disp('EEEK!');
Dawn@4:         pause;
Dawn@4:     end
Dawn@4: 
Dawn@4:     % determine whether we have a male, female or trans sample
Dawn@4:     gender( fileCount ) = '?';
Dawn@4:     if( ~(isempty(strfind(thestr,'fem'))))
Dawn@4:         % gender is female
Dawn@4:         gender( fileCount ) = 'F';
Dawn@4:     elseif( ~(isempty(strfind(thestr,'male'))))
Dawn@4:         % gender is male
Dawn@4:         gender( fileCount ) = 'M';
Dawn@4:     elseif( ~(isempty(strfind(thestr,'trans'))))
Dawn@4:         % gender is trans
Dawn@4:         gender( fileCount ) = 'T';
Dawn@4:     else
Dawn@4:         disp('EEEK!');
Dawn@4:         pause;
Dawn@4:     end
Dawn@4: 
Dawn@4:     %how many values are in the string?
Dawn@4:     spaces = strfind( thestr, ' ' );
Dawn@4:     numberstr = thestr( spaces(1) : end ); % chop off the file name  
Dawn@4:     vars = sscanf( numberstr, '%f', inf );
Dawn@4:     data( fileCount, : ) = vars;
Dawn@4:         
Dawn@4:     lineCount = lineCount + 1;
Dawn@4:     
Dawn@4: end
Dawn@4: fclose(inputFileID);
Dawn@4: 
Dawn@4: % ------------  apply the SVM classifier  ------------------------
Dawn@4: 
Dawn@4: G1E1 = []; G1E2 = []; G2E1 = []; G2E2 = []; UE1 = []; UE2 = [];
Dawn@4: 
Dawn@4: noOfIterations = 10;
Dawn@4: 
Dawn@4: for n = 1:noOfIterations
Dawn@4:     % Randomly select training and test sets
Dawn@4:     [train, test] = crossvalind('holdOut',groups);
Dawn@4:     cp = classperf(groups);
Dawn@4:     
Dawn@4:     % Use a linear support vector machine classifier
Dawn@4:     svmStruct = svmtrain(data(train,:),groups(train),'showplot',true);
Dawn@4:     classes = svmclassify(svmStruct,data(test,:),'showplot',true);
Dawn@4:     % See how well the classifier performed
Dawn@4:     classperf(cp,classes,test);
Dawn@4:     numbers = cp.CountingMatrix;
Dawn@4: 
Dawn@4:     G1E1(n) = numbers(1,1);
Dawn@4:     G1E2(n) = numbers(1,2);
Dawn@4:     G2E1(n) = numbers(2,1);
Dawn@4:     G2E2(n) = numbers(2,2);
Dawn@4:     UE1(n) = numbers(3,1);
Dawn@4:     UE2(n) = numbers(3,2);
Dawn@4:     
Dawn@4: end
Dawn@4: 
Dawn@4: G1E1 = sum(G1E1) / noOfIterations;
Dawn@4: G1E2 = sum(G1E2) / noOfIterations;
Dawn@4: G2E1 = sum(G2E1) / noOfIterations;
Dawn@4: G2E2 = sum(G2E2) / noOfIterations;
Dawn@4: % 
Dawn@4: % fprintf( fileOutputID, '\n' );
Dawn@4: % fclose( fileOutputID );
Dawn@4: % fprintf( fileSVMOutputID, '\n' );
Dawn@4: % fclose( fileKMeansOutputID );
Dawn@4: fprintf( masterFileOutputID, '\n' );
Dawn@4: fclose( masterFileOutputID );
Dawn@4: 
Dawn@4: end
Dawn@4: 
Dawn@4: