Hi I was reading the API of Spark 2.2.0 and noticed a change compared to 2.1.0
Compared to https://spark.apache.org/docs/2.1.0/api/scala/index.html#org.apache.spark.ml.classification.LogisticRegression the 2.2.0 docs at https://spark.apache.org/docs/2.2.0/api/scala/index.html#org.apache.spark.ml.classification.LogisticRegression mention that "This class supports fitting traditional logistic regression model by LBFGS/OWLQN and bound (box) constrained logistic regression model by LBFGSB." I went through the release notes and found that bound box constrain was added in 2.2. I wanted to know whether LBFGS was the default in Spark 2.1.0. If not, can we use LBFGS in Spark 2.1.0 or do we have to upgrade to 2.2.0?
