I'm trying to perform a random forest in R on a dataset with 16364 observations (after undersampling), using the function randomForest(). But my results look really weird:
What could have caused this? My data was very unbalanced at first, why I used undersampling. Maybe I don't understand undersampling correctly. My impression when I read about it was that if the minority class contains n observations, then you could just randomly sample n observations from the majority class and then combine the observations of the minority class with this new subset of the majority class, to get a new balanced dataset.
Before I used undersampling, the OOB was very low but the minority class was very poorly classified.
I would be most grateful if someone could help me realise what's wrong here, thank you in advance!