Github user sethah commented on the issue:
https://github.com/apache/spark/pull/18610
A couple questions:
1. do we actually *need* to save the initialModel when we persist the
current model? I'm not sure it's necessary and it adds complexity. Also, we
could add it in the future anyway.
2. How can users set an initial model from an array of coefficients? If
initialModel has to be a `LinearRegressionModel` then how can I create one from
an array? The model constructor is private... If you can only set an initial
model that was trained in Spark and saved as a Spark model, then that severely
limits the utility of this functionality. Can we just overload the set method?
````scala
final val initialModel: Param[Vector]
def setInitialModel(value: Vector) = ...
def setInitialModel(value: LinearRegressionModel) =
setInitialModel(value.coefficients)
````
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