Comparing different classification results with different trainig and test data
Your question is unclear. If you're saying that you have datasets with different attributes then this answer is not relevant.

If you're saying that you've grouped your dataset by some similarity measure into different groups and then split every group into test and train subgroups then yes, you may have overfitting.

However, if you made a TEST dataset from the COMPLETE dataset which has mixed elements from the original groups and proportional to them, and then tested your model against this test dataset then your results should represent your complete dataset properly.