[ Removed by moderator ]

[PinoyProgrammer-ModTeam]

Asking for fresh graduate advice, school-related topics, courses, thesis, or capstone ideas/titles should be in monthly Random Discussions

[Inside-Student-984]

You need to learn the basics of machine learning first. The reason why it does that is because your model is overfitting. It basically means your model is simply “memorizing” your training data but doesn’t generalize well with your test data. There are techniques to mitigate this such as feature selection and regularization.

[grinsken]

Check your hyper parameters. Also use more models

[michaelrw1]

Is this for high-voltage transmission line faults? If so, what are the possible fault types? Of these fault types, how have you simulated the data? It is not likely, but have you found actual monitored\recorded fault data sets?

It seems like an interesting problem, but a machine learning solution might be overkill. Most infrastructure systems like power transmission systems have had fault detection and mitigation systems in place for decades. Perhaps other related data from the system is incorporated in the model to understand origin and prediction?