[MRG+2] referred reliability diagrams and added citations #8527
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amueller
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Mar 4, 2017
sklearn/calibration.py
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| @@ -511,7 +511,8 @@ def predict(self, T): | |||
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| def calibration_curve(y_true, y_prob, normalize=False, n_bins=5): | |||
| """Compute true and predicted probabilities for a calibration curve. | |||
| """Compute true and predicted probabilities for a calibration curve also | |||
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The first line in the docstring should be a single line (keep forgetting the pep number for this).
Please add the sentence as a separate remark.
amueller
reviewed
Mar 4, 2017
doc/modules/calibration.rst
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| @@ -118,7 +118,7 @@ is evaluated with Brier score :func:`brier_score_loss`, reported in the legend | |||
| :align: center | |||
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| One can observe here that logistic regression is well calibrated as its curve is | |||
| nearly diagonal. Linear SVC's calibration curve has a sigmoid curve, which is | |||
| nearly diagonal. Linear SVC's calibration curve or reliability diagram has a sigmoid curve, which is | |||
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you should break at 80 characters.
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Fixed the PEP 257 conventions. Sorry about that! |
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LGTM |
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LGTM as well, let's see what travis and appveyor have to say. |
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Thanks @mehak-sachdeva |
Codecov Report
@@ Coverage Diff @@
## master #8527 +/- ##
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+ Coverage 95.48% 95.48% +<.01%
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Files 342 342
Lines 60913 60987 +74
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+ Hits 58160 58233 +73
- Misses 2753 2754 +1
Continue to review full report at Codecov.
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Reference Issue
Fixes #8423
What does this implement/fix? Explain your changes.
Added reliability diagram references in the docs and modified method docstring to reflect the same.
Also added citations to
Wilks, 1995for seminal paper on reliability diagram methodsAny other comments?
Easy fix to docs - sprint 03.04.2017