I have training instances that come from different sources so building one model doesn't work well. Is there a known method to use in such cases?
Example explains best. Let's say I want to classify cancer/non-cancer given training data that was constructed based on different populations. Training instances from one population might have a completely different distribution of positive/negative examples than in other populations. Now, I can build a separate model for each population, but the problem is that for testing I don't know from which population the test instance is coming from.
*all training/testing instances have the exact same feature set regardless of the population they came from.
Thanks a lot!