Hello everyone! I want to ask a question. I'm using the Performance (Binomial Classification) in Cross Validation while designing my model. From RapidMiner Documentation, I know the result in the picture below is using Confusion Matrix. If we count the Recall (TP/(TP+FN)) the result is 94,29% (similiar with the number in the picture). Then if we count the precision (TP/(TP+FP)) the result is 77,34% (also similiar with the number in the picture). But what's actually the meaning of the number "69,47%" and "91,67%" in the picture below? I need your help. Thank you.