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https://issues.apache.org/jira/browse/SPARK-7146?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-7146:
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Target Version/s: (was: 2.2.0)
> Should ML sharedParams be a public API?
> ---------------------------------------
>
> Key: SPARK-7146
> URL: https://issues.apache.org/jira/browse/SPARK-7146
> Project: Spark
> Issue Type: Brainstorming
> Components: ML
> Reporter: Joseph K. Bradley
>
> Proposal: Make most of the Param traits in sharedParams.scala public. Mark
> them as DeveloperApi.
> Pros:
> * Sharing the Param traits helps to encourage standardized Param names and
> documentation.
> Cons:
> * Users have to be careful since parameters can have different meanings for
> different algorithms.
> * If the shared Params are public, then implementations could test for the
> traits. It is unclear if we want users to rely on these traits, which are
> somewhat experimental.
> Currently, the shared params are private.
> h3. UPDATED proposal
> * Some Params are clearly safe to make public. We will do so.
> * Some Params could be made public but may require caveats in the trait doc.
> * Some Params have turned out not to be shared in practice. We can move
> those Params to the classes which use them.
> *Public shared params*:
> * I/O column params
> ** HasFeaturesCol
> ** HasInputCol
> ** HasInputCols
> ** HasLabelCol
> ** HasOutputCol
> ** HasPredictionCol
> ** HasProbabilityCol
> ** HasRawPredictionCol
> ** HasVarianceCol
> ** HasWeightCol
> * Algorithm settings
> ** HasCheckpointInterval
> ** HasElasticNetParam
> ** HasFitIntercept
> ** HasMaxIter
> ** HasRegParam
> ** HasSeed
> ** HasStandardization (less common)
> ** HasStepSize
> ** HasTol
> *Questionable params*:
> * HasHandleInvalid (only used in StringIndexer, but might be more widely used
> later on)
> * HasSolver (used in LinearRegression and GeneralizedLinearRegression, but
> same meaning as Optimizer in LDA)
> *Params to be removed from sharedParams*:
> * HasThreshold (only used in LogisticRegression)
> * HasThresholds (only used in ProbabilisticClassifier)
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