Calculate the Median of the results from 100 Simulations

Hi. I have a code where I am running a Random Forest regression. I am running it 100 times. However, I am having difficulty calculating the median of the 100 trials.

The result I am looking for is located in the variable designated "impOOB".

For each run, there should be values in impOOB variable for 5 columns. For instance:

0.427417559041683 0.00894308188405568 0.141297948087486 0.222153283589539 0.200188127397237

For 100 runs of column 1, I need the median. The same for column 2, and so forth.

My code is as follows:

n = 100;
result = zeros(n,5);
for k=1:n
    X = readtable('TOPOonly.xlsx','PreserveVariableNames',true)
    Y = readtable('TotalComplaintsRF.xlsx','PreserveVariableNames',true)
    t = templateTree('NumVariablesToSample','all',...
        'PredictorSelection','interaction-curvature','Surrogate','on');
    
    Mdl = fitrensemble(X,Y,'Method','Bag','NumLearningCycles',200, ...
        'Learners',t);
    yHat = oobPredict(Mdl);
    R2 = corr(Mdl.Y,yHat)^2
    impOOB = oobPermutedPredictorImportance(Mdl);
    impOOB(impOOB<0) = 0;
    impOOB = impOOB./sum(impOOB)
    result(k) = 
    
    
end

I'll attach the files as well. I appreciate very much any help with this.

Answer 1

[Matt J]

impOOB=rand(100,5)

impOOB = 100×5

0.7604 0.5152 0.7196 0.2418 0.5420 0.8386 0.3787 0.4701 0.4692 0.7572 0.9929 0.0561 0.2087 0.1176 0.9434 0.7796 0.2491 0.1337 0.1499 0.9048 0.3695 0.1500 0.6826 0.4575 0.4751 0.6069 0.1207 0.8111 0.5832 0.3273 0.9885 0.2647 0.1840 0.9606 0.0610 0.1243 0.3249 0.5171 0.1649 0.9400 0.7085 0.7869 0.5282 0.5472 0.4634 0.7656 0.4034 0.7932 0.8618 0.5136

median(impOOB,1)

ans = 1×5

0.4813 0.4997 0.4696 0.4513 0.5518

[CMatlabWold]

Thanks, but I think it is just taking the median of the last simulation run. I wanted to record all the simulation runs and find the median of each column for those.

[Matt J]

n = 100;
result = zeros(n,5);
for k=1:n
    X = readtable('TOPOonly.xlsx','PreserveVariableNames',true)
    Y = readtable('TotalComplaintsRF.xlsx','PreserveVariableNames',true)
    t = templateTree('NumVariablesToSample','all',...
        'PredictorSelection','interaction-curvature','Surrogate','on');
    
    Mdl = fitrensemble(X,Y,'Method','Bag','NumLearningCycles',200, ...
        'Learners',t);
    yHat = oobPredict(Mdl);
    R2 = corr(Mdl.Y,yHat)^2
    impOOB = oobPermutedPredictorImportance(Mdl);
    impOOB(impOOB<0) = 0;
    
    result(k,:) = impOOB./sum(impOOB);

end

median(result,1)

[CMatlabWold]

It works. Thank you very much