Updated false positve and false negative rate functions in functional.py #855
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
false positve and false negative rate functions to increase clarity for further usage, the two functions can be derived from already written sensitivity and specificity functions. Merging these into single ones, will help user to generalize all the metrics easily.
|
This PR is stale because it has been open 60 days with no activity. Remove stale label or comment or this will be closed in 15 days. |
|
@vermavinay982 Thanks for a PR 👍 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
In the segmentation metrics, the false positve and false negative rate functions are replaced, and implemented using default functions.
It will increase clarity for further usage, as the two functions can be derived from already written sensitivity and specificity functions. Merging these into single ones, will help user to generalize all the metrics easily without getting into raw calculations.