Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/11519#issuecomment-192470061
Hi, @srowen .
According to your advice, I reviewed the other algorithms and I found that
all other algorithms use the same default values for `reqParam` in
Scala/Python. It's a good new.
* ALS: 0.1
* LassoWithSGD: 0.01
* LinearRegression: 0.0
* LinearRegressionWithSGD: 0.0
* LogisticRegression: 0.0
* LogisticRegressionWithSGD: 0.01
* LogisticRegressionWithLBFGS: 0.00
* RidgeRegressionWithSGD: 0.01
* SVMWithSGD: 0.01
* StreamingLogisticRegressionWithSGD: 0.0
However, I found that `LinearRegressionWithSGD` and
`StreamingLinearRegressionWithSGD` does not have `regParam` as constructor
arguments. They just depends on `GradientDescent`'s default `reqParam` values.
So, I think we need to file this as a new JIRA issue.
Thank you, @srowen .
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