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Tamas Jambor commented on SPARK-2495: ------------------------------------- hi all, what's the reason MatrixFactorizationModel is still private? I am building a workflow similar to what Alexander described above and run into the same problem with MatrixFactorizationModel. There should be a point where it is accessible to store and recreate the model. > Ability to re-create ML models > ------------------------------ > > Key: SPARK-2495 > URL: https://issues.apache.org/jira/browse/SPARK-2495 > Project: Spark > Issue Type: Improvement > Components: MLlib > Affects Versions: 1.0.1 > Reporter: Alexander Albul > Assignee: Alexander Albul > Fix For: 1.1.0 > > > Hi everyone. > Previously (prior to Spark 1.0) we was working with MLib like this: > 1) Calculate model (costly operation) > 2) Take model and collect it's fields like weights, intercept e.t.c. > 3) Store model somewhere in our format > 4) Do predictions by loading model attributes, creating new model and > predicting using it. > Now i see that model's constructors have *private* modifier and cannot be > created from outside. > If you want to hide implementation details and keep this constructor as > "developer api", why not to create at least method, which will take weights, > intercept (for example) an materialize that model? > A good example of model that i am talking about is: *LinearRegressionModel* > I know that *LinearRegressionWithSGD* class have *createModel* method but the > problem is that it have *protected* modifier as well. -- 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