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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