-
Notifications
You must be signed in to change notification settings - Fork 64
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
Built in outlier detection #382
Comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Due to Garbage Collection, scheduling and load on the system we can get outliers in our measurements that impact esp. the average a lot. That happens esp. a lot with nano-second level benchmarks as even a 1ms gap is huge for them.
I'm no expert not 100% sure what to use, but I already wanted to support more data calculated by benchee itself for box plots (so to run less JS which makes this not be able to be opened). I talk about it here (I had forgotten): https://www.youtube.com/watch?v=C4hqcLwxs3A&t=1398s
But basically, as far as I understand p75 - p25 is the inter quantile range (IQR) and everything that is more than 1.5 IQR removed from p75 or p25 are considered outliers.
Skimming over wikipedia, that description seems accurate: https://en.wikipedia.org/wiki/Box_plot (Elements --> Whiskers)
We could run this statistical analysis once, remove the offending values and then rerun statistics calculation.
I think this should be opt in behavior (so default to false).
Kudos to the elixirforum post to remind me that we didn't yet have an issue for this.
The text was updated successfully, but these errors were encountered: