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Clip small positive values in gamma-nloglik #6537

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merged 1 commit into from
Dec 21, 2020

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gorkemozkaya
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For the gamma-nloglik eval metric, small positive values in the labels are causing NaN's in the outputs, as reported here: #5349. This will add clipping on them, similar to what is done in other metrics like poisson-nloglik and logloss.

For the `gamma-nloglik` eval metric, small positive values in the labels are causing `NaN`'s in the outputs, as reported here: dmlc#5349. This will add clipping on them, similar to what is done in other metrics like `poisson-nloglik` and `logloss`.
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codecov-io commented Dec 21, 2020

Codecov Report

Merging #6537 (0ed3370) into master (fbb980d) will increase coverage by 80.18%.
The diff coverage is n/a.

Impacted file tree graph

@@             Coverage Diff             @@
##           master    #6537       +/-   ##
===========================================
+ Coverage        0   80.18%   +80.18%     
===========================================
  Files           0       13       +13     
  Lines           0     3558     +3558     
===========================================
+ Hits            0     2853     +2853     
- Misses          0      705      +705     
Impacted Files Coverage Δ
python-package/xgboost/__init__.py 89.47% <0.00%> (ø)
python-package/xgboost/data.py 57.05% <0.00%> (ø)
python-package/xgboost/compat.py 72.54% <0.00%> (ø)
python-package/xgboost/libpath.py 55.55% <0.00%> (ø)
python-package/xgboost/tracker.py 93.98% <0.00%> (ø)
python-package/xgboost/callback.py 80.33% <0.00%> (ø)
python-package/xgboost/config.py 100.00% <0.00%> (ø)
python-package/xgboost/training.py 95.65% <0.00%> (ø)
python-package/xgboost/rabit.py 76.19% <0.00%> (ø)
python-package/xgboost/sklearn.py 89.48% <0.00%> (ø)
... and 3 more

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Thanks for the PR!

@trivialfis trivialfis merged commit 2231940 into dmlc:master Dec 21, 2020
honzasterba pushed a commit to h2oai/xgboost that referenced this pull request Feb 22, 2021
For the `gamma-nloglik` eval metric, small positive values in the labels are causing `NaN`'s in the outputs, as reported here: dmlc#5349. This will add clipping on them, similar to what is done in other metrics like `poisson-nloglik` and `logloss`.
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3 participants