PredictingPRNGs/exampleRandomForest.m at master · YashaPushak/PredictingPRNGs · GitHub

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clear

for i = 1

     n = 1000;
    v = 1000;
    t = 1000;
    d = 12;
    k = 5;
    featureType = 's';
    labelSize = 1;
    seed= 0;
    PRNGtype = 'yasha';

    [X,y,Xval, Yval, Xtest,ytest] = PRNGs(PRNGtype, n, v, t, d, k, featureType, labelSize, seed);

% Compute validation error with bootstrapped decision tree
    depth = 4;
    nTrees = 100;
    model = randomForest(X,y,depth,nTrees);
    yhat = model.predict(model,Xtest);

    if(labelSize ==1 )
        err(i) = sum(yhat ~= ytest)/t;
    else
        err(i) = 1-sum(all(yhat' == ytest'))/t;
    end

    disp(['iteration: ' num2str(i) ]);
    fprintf('Average Error for Random Forest: %.04f \n', mean(err));
    fprintf('Median Error for Random Forest: %.04f \n', median(err));

    if(mod(i,100) == 0)
        cdfplot(err);
        pause(0.1);
    end

end

fprintf('Average Error for Random Forest: %.04f \n', mean(err));
fprintf('Median Error for Random Forest: %.04f \n', median(err));
cdfplot(err);