Go it from a friend - println(model.weights) and println(model.intercept).
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Excellent, many thanks. Really appreciate your help.
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Original message From: Xiangrui Meng
Date:11/03/2014 9:04 PM (GMT-08:00)
To: Sameer Tilak Cc:
user@spark.apache.org Subject: Re: Model characterization
We recently added metrics for regression:
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RegressionMetrics.scala
and you can use
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificatio
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