fix: LIME sometimes return NaN weights #1112
Merged
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
|
/azp run |
|
Azure Pipelines successfully started running 1 pipeline(s). |
memoryz
force-pushed
the
jasowang/lime_fix
branch
from
03c72a1
to
3c8df62
Compare
|
/azp run |
|
Azure Pipelines successfully started running 1 pipeline(s). |
Codecov Report
@@ Coverage Diff @@
## master #1112 +/- ##
==========================================
+ Coverage 85.68% 85.72% +0.03%
==========================================
Files 251 251
Lines 11603 11604 +1
Branches 600 592 -8
==========================================
+ Hits 9942 9947 +5
+ Misses 1661 1657 -4
Continue to review full report at Codecov.
|
|
/azp run |
|
Azure Pipelines successfully started running 1 pipeline(s). |
|
/azp run |
|
Azure Pipelines successfully started running 1 pipeline(s). |
mhamilton723
approved these changes
Jul 3, 2021
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Outdated suggestions cannot be applied.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.
For categorical variables, if the LIME tabular sampler created samples that do not equal the original value for all simulated samples, we end up with an all zero variable, causing NaN weights. The fix is to simply append the original row as an identity sample to the simulated samples, making sure we don't end up with an all zero variable.