In a Random Forest, I know that the Out Of Bag Error is described as the fraction of number incorrect classifications over number of out of bag samples.
Accuracy is defined as the number of correct classifications divided by the number of samples.
It seems to me like a good way to remember these is:
OOB Error = 1 - Accuracy
But, I just want to check before I teach this. Can someone please tell me what the difference is between these?