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Combining (classified) example sets
I have a pretty straightforward classification task, and I'm experimenting with a variety of classifiers (thanks for making this so easy!).
Unfortunately, because of overlap in the features of my training data, I can not use straight cross-validation—if I were to, some data from my training would leak into the test set. So: I've created five splits of my data, training and test pairs which have no overlap. I've set up five replicated model learning and application, so now I have the classified output of these five models.
Here is my question: What block can I use to merge the resulting example sets so I can have one overall performance measure? Using the "Append" set operation does't work because the attributes aren't matched (is this because the example sets include both real and categorical?).