[ML] Fix possible cause for "Bad variance scale nan" log errors #1225
Conversation
This file contains hidden or 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
tveasey
changed the title
droberts195
approved these changes
May 11, 2020
tveasey
added a commit
to tveasey/ml-cpp-1
that referenced
this pull request
May 11, 2020
tveasey
added a commit
to tveasey/ml-cpp-1
that referenced
this pull request
May 11, 2020
tveasey
added a commit
that referenced
this pull request
May 11, 2020
tveasey
added a commit
that referenced
this pull request
May 12, 2020
tveasey
added a commit
to tveasey/ml-cpp-1
that referenced
this pull request
May 15, 2020
tveasey
added a commit
that referenced
this pull request
May 15, 2020
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Outdated suggestions cannot be applied.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.
Following on from #1114, there are a couple of places where we have code which could in theory generate 0/0. These would be a candidate root cause for #364 along with #1157.
This should generally have no impact on results until we'd actually hit the problem case.