[MRG+1] learning_curve takes error_score parameter and propagates it.#7397
Merged
NelleV merged 1 commit intoscikit-learn:masterfrom Sep 30, 2016
Merged
Conversation
Member
|
LGTM |
Member
|
Thanks! |
TomDLT
pushed a commit
to TomDLT/scikit-learn
that referenced
this pull request
Oct 3, 2016
amueller
pushed a commit
to amueller/scikit-learn
that referenced
this pull request
Oct 14, 2016
Sundrique
pushed a commit
to Sundrique/scikit-learn
that referenced
this pull request
Jun 14, 2017
paulha
pushed a commit
to paulha/scikit-learn
that referenced
this pull request
Aug 19, 2017
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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Reference Issue
Fixes #7370
What does this implement/fix? Explain your changes.
Learning curve will fail in some cases (not produce a learning curve). For example if using an estimator that raises when only one class is present - this may happen for the first iterations (small number of training samples). To fix this, learning_curve now takes error_score as a parameter and propagates it, the parameter's default value in learning_curve is 'raise' so the current behavior of failing is maintained - but this gives the option to set it to a value and have a learning_curve produced despite it failing for some iterations.
Any other comments?
This change is