I would like to compare different implementations of linear regression (and
possibly generalised linear regression) in Spark. I was wondering why the
functions for linear regression (and GLM) with stochastic gradient descent
have been deprecated?
I have found some old posts of people having problems with
LinearRegressionSGD and saying that it it slower than L-BFGS but I am not
sure what they mean. Shouldn’t SGD be better? Is there any plan to make
those functions available again in the new DataFrame-based API?