[jira] [Updated] (SPARK-4766) ML Estimator Params should subclass Transformer Params
[
https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley updated SPARK-4766:
-
Target Version/s: 1.4.0 (was: 1.3.0)
ML Estimator Params should subclass Transformer Params
--
Key: SPARK-4766
URL: https://issues.apache.org/jira/browse/SPARK-4766
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.2.0
Reporter: Joseph K. Bradley
Currently, in spark.ml, both Transformers and Estimators extend the same
Params classes. There should be one Params class for the Transformer and one
for the Estimator, where the Estimator params class extends the Transformer
one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
It's also weird to be able to:
* Wrap LogisticRegressionModel (a Transformer) with CrossValidator
* Pass a set of ParamMaps to CrossValidator which includes parameter
LogisticRegressionModel.maxIter
* (CrossValidator would try to set that parameter.)
* I'm not sure if this would cause a failure or just be a noop.
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[jira] [Updated] (SPARK-4766) ML Estimator Params should subclass Transformer Params
[
https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley updated SPARK-4766:
-
Description:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
It's also weird to be able to:
* Wrap LogisticRegressionModel (a Transformer) with CrossValidator
* Pass a set of ParamMaps to CrossValidator which includes parameter
LogisticRegressionModel.maxIter
* (CrossValidator would try to set that parameter.)
* I'm not sure if this would cause a failure or just be a noop.
was:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
(This is the only case where this happens currently, but it is worth setting a
precedent.)
ML Estimator Params should subclass Transformer Params
--
Key: SPARK-4766
URL: https://issues.apache.org/jira/browse/SPARK-4766
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.2.0
Reporter: Joseph K. Bradley
Currently, in spark.ml, both Transformers and Estimators extend the same
Params classes. There should be one Params class for the Transformer and one
for the Estimator, where the Estimator params class extends the Transformer
one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
It's also weird to be able to:
* Wrap LogisticRegressionModel (a Transformer) with CrossValidator
* Pass a set of ParamMaps to CrossValidator which includes parameter
LogisticRegressionModel.maxIter
* (CrossValidator would try to set that parameter.)
* I'm not sure if this would cause a failure or just be a noop.
--
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[jira] [Updated] (SPARK-4766) ML Estimator Params should subclass Transformer Params
[
https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley updated SPARK-4766:
-
Assignee: (was: Joseph K. Bradley)
ML Estimator Params should subclass Transformer Params
--
Key: SPARK-4766
URL: https://issues.apache.org/jira/browse/SPARK-4766
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.2.0
Reporter: Joseph K. Bradley
Currently, in spark.ml, both Transformers and Estimators extend the same
Params classes. There should be one Params class for the Transformer and one
for the Estimator, where the Estimator params class extends the Transformer
one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
--
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[jira] [Updated] (SPARK-4766) ML Estimator Params should subclass Transformer Params
[
https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley updated SPARK-4766:
-
Description:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
(This is the only case where this happens currently, but it is worth setting a
precedent.)
was:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
ML Estimator Params should subclass Transformer Params
--
Key: SPARK-4766
URL: https://issues.apache.org/jira/browse/SPARK-4766
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.2.0
Reporter: Joseph K. Bradley
Currently, in spark.ml, both Transformers and Estimators extend the same
Params classes. There should be one Params class for the Transformer and one
for the Estimator, where the Estimator params class extends the Transformer
one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
(This is the only case where this happens currently, but it is worth setting
a precedent.)
--
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[jira] [Updated] (SPARK-4766) ML Estimator Params should subclass Transformer Params
[
https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joseph K. Bradley updated SPARK-4766:
-
Description:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
was:
Currently, in spark.ml, both Transformers and Estimators extend the same Params
classes. There should be one Params class for the Transformer and one for the
Estimator, where the Estimator params class extends the Transformer one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.setMaxIter(10)
{code}
ML Estimator Params should subclass Transformer Params
--
Key: SPARK-4766
URL: https://issues.apache.org/jira/browse/SPARK-4766
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 1.2.0
Reporter: Joseph K. Bradley
Currently, in spark.ml, both Transformers and Estimators extend the same
Params classes. There should be one Params class for the Transformer and one
for the Estimator, where the Estimator params class extends the Transformer
one.
E.g., it is weird to be able to do:
{code}
val model: LogisticRegressionModel = ...
model.getMaxIter()
{code}
--
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