SVMWithSGD sits in the older "mllib" package and is not compatible directly
with the DataFrame API. I suppose one could write a ML-API wrapper around
it.
However, there is LinearSVC in Spark 2.2.x:
http://spark.apache.org/docs/latest/ml-classification-regression.html#linear-support-vector-machine
Hello,
is there any way to use CrossValidation's ParamGrid with SVMWithSGD?
usually, when e.g. using RandomForest you can specify a lot of parameters,
to automatise the param grid search (when used with CrossValidation)
val algorithm = new RandomForestClassifier()
val paramGrid = { new
