Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1397#discussion_r50391309
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/regression/MultipleLinearRegression.scala
---
@@ -107,6 +107,11 @@ class MultipleLinearRegression extends
Predictor[MultipleLinearRegression] {
this
}
+ def setOptimizationMethod(optimizationMethod: String): this.type = {
--- End diff --
Furthermore, if you expose the optimization method, then you should also
expose the decay parameter. But to be honest I'm not so sure whether this is
the right way to do, because you would have to add to every algorithm every new
parameter of the underlying solver. I guess it would be better to expose a
parameter where you can set a non-default solver which allows you to set these
things directly. What do you think?
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