I don't think that there's an existing function that does that for you, so you have to build your own. Here is a suggested method:
- Assuming you have your five prediction arrays from your five different classifiers, and
- all prediction arrays have the same size = length(test_rows), and
- you have 2 classes: 1 & 2, you can do the following:
% First we concatenate all prediciton arrays into one big matrix.
% Make sure that all prediction arrays are of the same type, I am assumming here that they
% are type double. I am also assuming that all prediction arrays are column vectors.
Prediction = [svm,rforest,DTree,dt,sk];
Final_decision = zeros(length(test_rows),1);
all_results = [1,2]; %possible outcomes
for row = 1:length(test_rows)
election_array = zeros(1,2);
for col = 1:5 %your five different classifiers
election_array(Prediction(row,col)) = ...
election_array(Prediction(row,col)) + 1;
end
[~,I] = max(election_array);
Final_decision(row) = all_results(I);
end
Hope this helps.
Ahmad
