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

Interpretation of the Predictive Uncertainty for descision making #11

Open
akashmondal1810 opened this issue Jul 13, 2020 · 0 comments
Open

Comments

@akashmondal1810
Copy link

Hello,
In classification Is there any way to interpret the obtained Predictive Uncertainty? After computing the predictive uncertainty is there any way to calculate any threshold or cutoff value(as you have mentioned here:https://camo.githubusercontent.com/e78af0e93f0ea7cc80e38f7b9273486bbf6f37f6/687474703a2f2f7777772e63732e6f782e61632e756b2f70656f706c652f616e67656c6f732e66696c6f732f6173736574732f62646c2d62656e63686d61726b732f646961676e6f7369732e706e67) so that if the predictive variance is above that value we can say that the model is uncertain or below which it is certain about its prediction?
Uncertain if (predictive variance>=threshold) || Certain if (predictive variance<threshold)
How to compute this threshold!
Thanks!

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

1 participant