Alexander Albul created SPARK-2495:
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Summary: 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
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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