[ML] Linear regression with SGD

Hi, 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

Re: Linear Regression with SGD

, Stephen Carman scar...@coldlight.com wrote: Hi User group, We are using spark Linear Regression with SGD as the optimization technique and we are achieving very sub-optimal results. Can anyone shed some light on why this implementation seems to produce such poor results vs our own

Linear Regression with SGD

Hi User group, We are using spark Linear Regression with SGD as the optimization technique and we are achieving very sub-optimal results. Can anyone shed some light on why this implementation seems to produce such poor results vs our own implementation? We are using a very small dataset

Re: Linear Regression with SGD

with an equivalent R implementation. On 9 Jun 2015, at 22:05, Stephen Carman scar...@coldlight.com wrote: Hi User group, We are using spark Linear Regression with SGD as the optimization technique and we are achieving very sub-optimal results. Can anyone shed some light on why this implementation

Re: Linear Regression with SGD

-size. In 1.4 there is an implementation of ElasticNet Linear Regression which is supposed to compare favourably with an equivalent R implementation. On 9 Jun 2015, at 22:05, Stephen Carman scar...@coldlight.com wrote: Hi User group, We are using spark Linear Regression with SGD