[SPARK-33592][ML][PYTHON][3.0] Backport Fix: Pyspark ML Validator params in estimatorParamMaps may be lost after saving and reloading #30590
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…may be lost after saving and reloading
Fix: Pyspark ML Validator params in estimatorParamMaps may be lost after saving and reloading
When saving validator estimatorParamMaps, will check all nested stages in tuned estimator to get correct param parent.
Two typical cases to manually test:
~~~python
tokenizer = Tokenizer(inputCol="text", outputCol="words")
hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol="features")
lr = LogisticRegression()
pipeline = Pipeline(stages=[tokenizer, hashingTF, lr])
paramGrid = ParamGridBuilder() \
.addGrid(hashingTF.numFeatures, [10, 100]) \
.addGrid(lr.maxIter, [100, 200]) \
.build()
tvs = TrainValidationSplit(estimator=pipeline,
estimatorParamMaps=paramGrid,
evaluator=MulticlassClassificationEvaluator())
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
~~~
~~~python
lr = LogisticRegression()
ova = OneVsRest(classifier=lr)
grid = ParamGridBuilder().addGrid(lr.maxIter, [100, 200]).build()
evaluator = MulticlassClassificationEvaluator()
tvs = TrainValidationSplit(estimator=ova, estimatorParamMaps=grid, evaluator=evaluator)
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
~~~
Bug fix.
No
Unit test.
Closes apache#30539 from WeichenXu123/fix_tuning_param_maps_io.
Authored-by: Weichen Xu <weichen.xu@databricks.com>
Signed-off-by: Ruifeng Zheng <ruifengz@foxmail.com>
(cherry picked from commit 8016123)
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
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…ams in estimatorParamMaps may be lost after saving and reloading
Fix: Pyspark ML Validator params in estimatorParamMaps may be lost after saving and reloading
When saving validator estimatorParamMaps, will check all nested stages in tuned estimator to get correct param parent.
Two typical cases to manually test:
~~~python
tokenizer = Tokenizer(inputCol="text", outputCol="words")
hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol="features")
lr = LogisticRegression()
pipeline = Pipeline(stages=[tokenizer, hashingTF, lr])
paramGrid = ParamGridBuilder() \
.addGrid(hashingTF.numFeatures, [10, 100]) \
.addGrid(lr.maxIter, [100, 200]) \
.build()
tvs = TrainValidationSplit(estimator=pipeline,
estimatorParamMaps=paramGrid,
evaluator=MulticlassClassificationEvaluator())
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
~~~
~~~python
lr = LogisticRegression()
ova = OneVsRest(classifier=lr)
grid = ParamGridBuilder().addGrid(lr.maxIter, [100, 200]).build()
evaluator = MulticlassClassificationEvaluator()
tvs = TrainValidationSplit(estimator=ova, estimatorParamMaps=grid, evaluator=evaluator)
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
~~~
Bug fix.
No
Unit test.
Closes #30539 from WeichenXu123/fix_tuning_param_maps_io.
Authored-by: Weichen Xu <weichen.xudatabricks.com>
Signed-off-by: Ruifeng Zheng <ruifengzfoxmail.com>
(cherry picked from commit 8016123)
Signed-off-by: Weichen Xu <weichen.xudatabricks.com>
### What changes were proposed in this pull request?
### Why are the changes needed?
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Closes #30590 from WeichenXu123/SPARK-33592-bp-3.0.
Authored-by: Weichen Xu <weichen.xu@databricks.com>
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
|
Merged to branch-3.0 |
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Fix: Pyspark ML Validator params in estimatorParamMaps may be lost after saving and reloading
When saving validator estimatorParamMaps, will check all nested stages in tuned estimator to get correct param parent.
Two typical cases to manually test:
Bug fix.
No
Unit test.
Closes #30539 from WeichenXu123/fix_tuning_param_maps_io.
Authored-by: Weichen Xu weichen.xu@databricks.com
Signed-off-by: Ruifeng Zheng ruifengz@foxmail.com
(cherry picked from commit 8016123)
Signed-off-by: Weichen Xu weichen.xu@databricks.com
What changes were proposed in this pull request?
Why are the changes needed?
Does this PR introduce any user-facing change?
How was this patch tested?