One other benefit of switching is, this API supports multi-class classification too. I've tested this API with Iris dataset.
On Sun, May 31, 2015 at 7:33 PM, Nirmal Fernando <[email protected]> wrote: > Hi, > > Currently in ML, we use mini-batch gradient descent algorithm when running > logistic regression. But Spark-mllib recommends L-BFGS over mini-batch > gradient descent for faster convergence [1]. > > I tested both the implementation with the same dataset and gained an > improved accuracy in L-BFGS (80% vs 67% for SGD). > > Shall we switch? > > [1] > https://spark.apache.org/docs/latest/mllib-linear-methods.html#logistic-regression > > > -- > > Thanks & regards, > Nirmal > > Associate Technical Lead - Data Technologies Team, WSO2 Inc. > Mobile: +94715779733 > Blog: http://nirmalfdo.blogspot.com/ > > > -- Thanks & regards, Nirmal Associate Technical Lead - Data Technologies Team, WSO2 Inc. Mobile: +94715779733 Blog: http://nirmalfdo.blogspot.com/
_______________________________________________ Dev mailing list [email protected] http://wso2.org/cgi-bin/mailman/listinfo/dev
