Hi everyone!
I’m trying to train an activity classification model with 3 classes. The problem is that only one class has precision and recall > 0 after training.
Even with 2 classes result is the same
First I’d thought that there is a problem with my data but when I switched “left” label to “right” and vice versa the results were the same: only “left”-labeled data get non-zero precision and recall.
So what's happening in all 3 cases is that your model is predicting "left" 100% of the time. This gives you a recall of 100% for that class only! So it's not a great model, because there's no separation between the different classes. It has an okay F1 score because it's really good at telling you that all left examples are left, but it's not really useful. Would you be able to provide some of the training data to take a closer look at? There's a couple different things that could be happening:
