Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Concern about F1-PA score #35

Open
devinbost opened this issue Mar 27, 2024 · 1 comment
Open

Concern about F1-PA score #35

devinbost opened this issue Mar 27, 2024 · 1 comment

Comments

@devinbost
Copy link

It looks like the F1 score and other metrics reported in the paper use the PA adjustment method.
I want to flag that this method has been shown to overestimate performance.

Kim, S., Choi, K., Choi, H. S., Lee, B., & Yoon, S. (2022, June). Towards a rigorous evaluation of time-series anomaly detection. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 7, pp. 7194-7201). Available here.

The issue is widespread in other papers and is being discussed in other projects, such as here: thuml/Anomaly-Transformer#65

It would be helpful to see an updated baseline that uses more robust methods for evaluating results.

@tianzhou2011
Copy link
Contributor

tianzhou2011 commented Mar 28, 2024 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants