Dear Team,
In your report, you provide the folowing details for each fold:
"Method Deep 3D Res18 Deep 3D DPN26 Fold 0 0.8610 0.8750 Fold 1 0.8538 0.8783 Fold 2 0.7902 0.8170 Fold 3 0.7863 0.7731 Fold 4 0.8795 0.8850 Fold 5 0.8360 0.8095 Fold 6 0.8959 0.8649 Fold 7 0.8700 0.8816 Fold 8 0.8886 0.8668 Fold 9 0.8041 0.8122"
Each of these numbers is evidently less than 0.9.
Later in the paper, you state that:
"R-CNN has a total recall rate 94.6% for all the detected nodules, while 3D DPN26 Faster R-CNN has a recall rate 95.8%."
How were these results calculated, e.g the quoted total recall rates of 94.6% and 95.8%. ?
If each results on each fold is less than 90% how can the average be more than 90%?
Dear Team, In your report, you provide the folowing details for each fold: "Method Deep 3D Res18 Deep 3D DPN26 Fold 0 0.8610 0.8750 Fold 1 0.8538 0.8783 Fold 2 0.7902 0.8170 Fold 3 0.7863 0.7731 Fold 4 0.8795 0.8850 Fold 5 0.8360 0.8095 Fold 6 0.8959 0.8649 Fold 7 0.8700 0.8816 Fold 8 0.8886 0.8668 Fold 9 0.8041 0.8122"
Each of these numbers is evidently less than 0.9.
Later in the paper, you state that: "R-CNN has a total recall rate 94.6% for all the detected nodules, while 3D DPN26 Faster R-CNN has a recall rate 95.8%."
How were these results calculated, e.g the quoted total recall rates of 94.6% and 95.8%. ? If each results on each fold is less than 90% how can the average be more than 90%?
Many thanks,