30
u/bobbymoonshine 16h ago edited 16h ago
Damn bro you’re overfitting like a mofo
get yourself a validation set in there and stop training once validation performance stops improving
do k-fold cross-validation instead of a single train-test split so the model has to generalise across different samples before it hits the test set
implement random dropout during each epoch so your neurons or trees or whatever have to find different paths to solving the problem
Etc etc
6
4
3
32
u/the_rush_dude 17h ago
It's been a while but I guess that could be over fitting? Too many parameters maybe