Change IDF formula #1141
Open
Change IDF formula #1141
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
Codecov ReportBase: 73.84% // Head: 73.84% // No change to project coverage 👍
Additional details and impacted files@@ Coverage Diff @@
## main #1141 /- ##
=======================================
Coverage 73.84% 73.84%
=======================================
Files 28 28
Lines 2294 2294
=======================================
Hits 1694 1694
Misses 600 600
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report at Codecov. |
|
Experimental verification required. |
|
it looks like it did maybe improve precision and recall for the restaurant dataset. why don't you re-open this and i can take a look at some other datasets. |
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Outdated suggestions cannot be applied.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.
Implement the change being discussed in #1140.
Also directly import
numpy.logto avoid attribute access inside for loop.