GNU Octave script to test my k-means algorithm using the iris data set

iris.m

% usage:
%       octave-cli iris.m
fid = fopen('iris.data');
irisTextData = textscan(fid,'%f %f %f %f %s', 200, 'Delimiter',',');
fclose (fid);
irisMatrix = cell2mat(irisTextData(:,1:4));
k = 3;

clusterID = kMeans(irisMatrix, k);

result = cell2mat(irisTextData(:,5));
for i = 1:size(result, 1)
    result(i, 2) = clusterID(i);
end


rightSampleCnt = 0;
clusterNameMap = cellstr(["Iris-virginica"; "Iris-versicolor"; "Iris-setosa"]);
for i = 1:size(result, 1)
    printf("%.1f %.1f %.1f %.1f %s\t%d", ...
        irisMatrix(i,:), cell2mat(result(i, 1)) , cell2mat(result(i, 2)) );
    if strcmp(result(i, 1), clusterNameMap(cell2mat(result(i, 2))) )
        rightSampleCnt = rightSampleCnt+1;
        % printf("  √");
    else
        printf("  X");
    end
    printf("\n");
end
printf("Total Sample: %d\nRight Sample: %d\nAccuracy: %f\n", ...
    size(result, 1), rightSampleCnt, rightSampleCnt / size(result, 1) );

% writetable(cell2table(result), 'result.csv') % only avaliable in Matlab 😒