For those unattended here is the Datathon link: https://dphi.tech/practice/challenge/49
Well, it is likely that we could face similar issues while solving real-world problems too. There are several cases where certain problems do not necessarily need to be solved with ML/A.I Maybe this is one such case.
Other potential reasons that are affecting performance:
- the data is not just adequate and we could’ve collected more data and most importantly more data elements (features).
- huge class imbalance
- and more… opening to hearing thoughts.
If your performance is bad don’t arrive at a conclusion that you are not good at solving. Instead, it is better to reason the root cause, fill the gaps and change the strategy (maybe even the training data isn’t adequate enough to solve this problem).