Re: MLlib - logistic regression with GD vs LBFGS, sparse vs dense benchmark result

Also, how many failure of rejection will terminate the optimization process? How is it related to numberOfImprovementFailures? Thanks. Sincerely, DB Tsai --- My Blog: https://www.dbtsai.com LinkedIn: https://www.linkedin.com/in/dbtsai On

Re: thoughts on spark_ec2.py?

Thanks for the info and good luck with 1.0. Regards, Art On Fri, Apr 25, 2014 at 9:48 AM, Andrew Or and...@databricks.com wrote: Hi Art, First of all thanks a lot for your PRs. We are currently in the middle of all the Spark 1.0 release so most of us are swamped with the more core

Re: MLlib - logistic regression with GD vs LBFGS, sparse vs dense benchmark result

That's right. FWIW, caching should be automatic now, but it might be the version of Breeze you're using doesn't do that yet. Also, In breeze.util._ there's an implicit that adds a tee method to iterator, and also a last method. Both are useful for things like this. -- David On Sun, Apr 27,

Re: MLlib - logistic regression with GD vs LBFGS, sparse vs dense benchmark result

Hi David, I got most of the stuff working, and the loss is monotonically decreasing by getting the history from iterator of state. However, in the costFun, I need to know what current iteration is it for miniBatch, which means for one iteration, if optimizer calls costFun several times for line