Quick question: I've been always told that if a binary classifier shows a very low accuracy (~0) you can switch the predictions to get an high accuracy (~1).
It actually never happened to me before, but now I have a Random Forests classifier which gives a prediction ~0. If I invert the predictions, then I get an accuracy ~1.
I'm trying to figure it out why at a certain point it decides to classify the data in class 1 as class 0, and vice versa.
Any idea what I should look for?
The classifier is the standard TreeBagger of MATLAB.