Closed TuanNguyen27 closed 4 years ago
Merging #494 into master will decrease coverage by
3.80%
. The diff coverage isn/a
.
@@ Coverage Diff @@
## master #494 +/- ##
==========================================
- Coverage 82.63% 78.83% -3.81%
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Files 345 345
Lines 11702 11702
Branches 388 388
==========================================
- Hits 9670 9225 -445
- Misses 2032 2477 +445
Impacted Files | Coverage Δ | |
---|---|---|
...scala/com/salesforce/op/utils/text/TextUtils.scala | 0.00% <0.00%> (-100.00%) |
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.../scala/com/salesforce/op/test/FeatureAsserts.scala | 0.00% <0.00%> (-100.00%) |
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...ala/com/salesforce/op/readers/CSVAutoReaders.scala | 0.00% <0.00%> (-100.00%) |
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...la/com/salesforce/op/test/TestFeatureBuilder.scala | 0.00% <0.00%> (-100.00%) |
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...om/salesforce/op/stages/impl/feature/OpNGram.scala | 0.00% <0.00%> (-100.00%) |
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...alesforce/op/stages/impl/feature/OpHashingTF.scala | 0.00% <0.00%> (-100.00%) |
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...lesforce/op/stages/impl/feature/LangDetector.scala | 0.00% <0.00%> (-100.00%) |
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...sforce/op/aggregators/CustomMonoidAggregator.scala | 0.00% <0.00%> (-100.00%) |
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...sforce/op/stages/base/binary/BinaryEstimator.scala | 0.00% <0.00%> (-100.00%) |
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...e/op/stages/impl/feature/TextMapLenEstimator.scala | 0.00% <0.00%> (-100.00%) |
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... and 111 more |
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Add a description of flakiness, and how your fix addresses it
Source of flakiness: default
BinaryClassificationModelSelector.withTrainValidationSplit
sometimes makes the training set contain only positive or negative labels, which fails the training for xgboost.We address this flakiness by fixing the seed in the
DataSplitter
forwithTrainValidationSplit
, which will result in the same train-test split every time the test is run.