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Joseph K. Bradley commented on SPARK-6682: ------------------------------------------ Builder methods for GLMs have issues because of the Optimizer API. (See discussion above: The constructors for Optimizer require Gradient and Updater.) Cleaning up the Optimizer API will facilitate moving to the builder API. > Deprecate static train and use builder instead for Scala/Java > ------------------------------------------------------------- > > Key: SPARK-6682 > URL: https://issues.apache.org/jira/browse/SPARK-6682 > Project: Spark > Issue Type: Improvement > Components: MLlib > Affects Versions: 1.3.0 > Reporter: Joseph K. Bradley > > In MLlib, we have for some time been unofficially moving away from the old > static train() methods and moving towards builder patterns. This JIRA is to > discuss this move and (hopefully) make it official. > "Old static train()" API: > {code} > val myModel = NaiveBayes.train(myData, ...) > {code} > "New builder pattern" API: > {code} > val nb = new NaiveBayes().setLambda(0.1) > val myModel = nb.train(myData) > {code} > Pros of the builder pattern: > * Much less code when algorithms have many parameters. Since Java does not > support default arguments, we required *many* duplicated static train() > methods (for each prefix set of arguments). > * Helps to enforce default parameters. Users should ideally not have to even > think about setting parameters if they just want to try an algorithm quickly. > * Matches spark.ml API > Cons of the builder pattern: > * In Python APIs, static train methods are more "Pythonic." > Proposal: > * Scala/Java: We should start deprecating the old static train() methods. We > must keep them for API stability, but deprecating will help with API > consistency, making it clear that everyone should use the builder pattern. > As we deprecate them, we should make sure that the builder pattern supports > all parameters. > * Python: Keep static train methods. > CC: [~mengxr] -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org