Please I really need your help on this guys [D]

My teacher gave us a machine learning time series classification problem.

At first, I tried solving it normally and got a public score of 0.85. But then I searched for the dataset used in the competition and managed to find it. Using that dataset, I generated a submission file that scored 1.00.

Now my question is:

Is it possible to recreate the submission file using only the provided train and test datasets, without relying on the external dataset I found?

In other words, I want to understand if there is a way to learn or reverse-engineer how to produce the same submission output (ID → label mapping) using only the original train/test files. I’m not sure if “reverse engineering the submission” is the correct term, but I want to figure out how to get the same result properly using machine learning rather than external data.

Also, I want to clarify that for the submission I made, I actually had access to the full feature set—not just IDs and labels, meaning the other feature of the sub file

I would really appreciate any help or guidance. If needed, I can share the train/test files or the submission file that achieved the 1.00 score.

Thanks in advance!