Per entity metric #63
Open
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
…v/webstruct into speed_up_text_tokenizer
Speed up text tokenizer
… various industries.
…es_from_files` to `load_trees`.
Codecov Report
@@ Coverage Diff @@
## master #63 +/- ##
==========================================
+ Coverage 81.02% 82.65% +1.62%
==========================================
Files 40 43 +3
Lines 2092 2300 +208
==========================================
+ Hits 1695 1901 +206
- Misses 397 399 +2 |
kmike
reviewed
Jun 27, 2018
| ) | ||
|
|
||
|
|
||
| def almost_equal(result, expected): |
There was a problem hiding this comment.
I think https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.allclose.html can cover it
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Outdated suggestions cannot be applied.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.
these metrics are measured independently from where in the page the entity has been extracted. It also it checks full match only:
accuracy(true = 'John Doe', pred = 'John' )= 0