[jira] [Commented] (SPARK-2495) Ability to re-create ML models

["Tamas Jambor (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-2495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14224894#comment-14224894 ] 

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.



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