In order to ensemble a decision tree, let me explain the specific situation. I have split the dataset in 5 sections, per protocol e.g. TCP, HTTP etc. Now I've trained a decision tree for each one and run this against my test dataset.
How do I go about combining the 5 prediction models. Do I....
a) combine the predicted output e.g. 1,0;1,1 for each section done separate and then run it against the test dataset to identify confusion matrix. This is actual class, predicted class.
b) do I take the tree build and then add the additional ones to the tree model, in effect combining them.
Which method should be suitable, would option a even be a good solution?