[MRG+1] more explicit error message when multiple scores passed #11008
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Thanks for the PR @minggli ! There is one test failing in |
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thanks! fixed. 😀 |
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LGTM. |
glemaitre
reviewed
Apr 22, 2018
sklearn/metrics/scorer.py
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| @@ -300,6 +300,10 @@ def check_scoring(estimator, scoring=None, allow_none=False): | |||
| "If no scoring is specified, the estimator passed should " | |||
| "have a 'score' method. The estimator %r does not." | |||
| % estimator) | |||
| elif isinstance(scoring, (list, tuple, set, dict)): | |||
There was a problem hiding this comment.
Can be more permissive and ducktype:
from collections import Iterable
...
elif isinstance(scoring, Iterable):
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And add an entry in the what's new as well. |
glemaitre
reviewed
Apr 22, 2018
doc/whats_new/v0.20.rst
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| @@ -204,6 +204,10 @@ Model evaluation and meta-estimators | |||
| return estimators fitted on each split. :issue:`9686` by :user:`Aurélien Bellet | |||
| <bellet>`. | |||
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| - Add improved error message in :func:`model_selection.cross_val_score` when | |||
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This should be in the Bug Fixes section instead
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LGTM |
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Thanks @minggli |
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happy to contribute! |
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Reference Issues/PRs
Fixes #11006. See also #3456.
What does this implement/fix? Explain your changes.
Add a more explicit message when one of below is passed to
scoring=keyword in cross_val_score: list, set, tuple, dict. It prompts user to use cross_validate for multiple metrics evaluation.Any other comments?