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/
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