Hi everyone,
I'm curious about the difference between
ml.classification.LogisticRegression and
mllib.classification.LogisticRegressionWithLBFGS. Both of them are
optimized using LBFGS, the only difference I see is LogisticRegression
takes DataFrame while LogisticRegressionWithLBFGS takes RDD.
So I wonder,
1. Why not simply add a DataFrame training interface to
LogisticRegressionWithLBFGS?
2. Whats the difference between ml.classification and
mllib.classification package?
3. Why doesn't ml.classification.LogisticRegression call
mllib.optimization.LBFGS / mllib.optimization.OWLQN directly? Instead,
it uses breeze.optimize.LBFGS and re-implements most of the procedures
in mllib.optimization.{LBFGS,OWLQN}.
Thank you.
Best,
--
Yizhi Liu
Senior Software Engineer / Data Mining
www.mvad.com, Shanghai, China
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