How to calculate % wrong bounding box and % misclassification?

[Shanky71]

I am confused how you are defining the wrong bounding boxes as the yolov5 with generate multiple bounding box.
If True positive: 88.6%
False positive: 9.6%
False negative: 11.4%
how can I calculate the % for wrong bounding box and misclassification separately. I checked manually about the % of misclassfication of the validation dataset , it came out as 0.64%, so does it mean I have 8.96% of wrong bounding boxes? To confirm this I used IOU overlapping between annotations of my validation dataset and generating the detections from yolov5, the mean IOU value came out to be 0.995. Why so much difference ?