Closed yaanolja closed 2 years ago
Hi, thank you for your comment.
tps_rs_unique
contains the number of True Positive segments of an algorithm results.
tps_gt_unique
contains the number of True Positive segments annotated that collide with tps_rs_unique
. The purpose of this number is to compute TP_event_ratio
. Let me know if you need more clarification on this.
Thanks for your explanation.
Hmm... I think the denominator of recall is the number of groundtruth('unanimity' tag in cross_annotations.csv). recall = tps_gt_unique / groundtruth_num
Hi again, you're right. In terms of number of matches recall is recall = len(tps_gt_unique) / (len(tps_gt_unique) + len(fns_gt_unique))
. The F1 score (in terms of number of matches) then does not make a lot of sense so I'll just remove it. I'll update the code soon. Thanks again for raising this issue.
Hi, marking this as compleated. Find the new code version here: https://github.com/guillemcortes/baf-dataset/commit/b406cf7dafac479a5ea2806e2910dd88761cf6cb
Thanks for sharing a good dataset.
The unique-recall calculation(compute_statistics.py) is as follows. recall = len(tps_rs_unique) / (len(tps_rs_unique) + len(fns_gt_unique))
I think tps_rs_unique should replaced with tps_gt_unique.