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.…