Re: Model characterization
Go it from a friend - println(model.weights) and println(model.intercept). -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Model-characterization-tp17985p18106.html Sent from the Apache Spark User List mailing list archive at Nabble.com. - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
Model characterization
Hi All, I have been using LinearRegression model of MLLib and very pleased with its scalability and robustness. Right now, we are just calculating MSE of our model. We would like to characterize the performance of our model. I was wondering adding support for computing things such as Confidence Interval etc. are they something that are on the roadmap? Graphical things such as ROC curves etc. will that be supported by MLLib/other parts of the ecosystem? or is this something for which other statistical packages are recommended?
