Yanbo Liang d81a71357e [SPARK-13545][MLLIB][PYSPARK] Make MLlib LogisticRegressionWithLBFGS's default parameters consistent in Scala and Python ... ## What changes were proposed in this pull request? * The default value of ```regParam``` of PySpark MLlib ```LogisticRegressionWithLBFGS``` should be consistent with Scala which is ```0.0```. (This is also consistent with ML ```LogisticRegression```.) * BTW, if we use a known updater(L1 or L2) for binary classification, ```LogisticRegressionWithLBFGS``` will call the ML implementation. We should update the API doc to clarifying ```numCorrections``` will have no effect if we fall into that route. * Make a pass for all parameters of ```LogisticRegressionWithLBFGS```, others are set properly. cc mengxr dbtsai ## How was this patch tested? No new tests, it should pass all current tests. Author: Yanbo Liang <ybliang8@gmail.com> Closes #11424 from yanboliang/spark-13545.		2016-02-29 00:55:51 -08:00
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src	[SPARK-13545][MLLIB][PYSPARK] Make MLlib LogisticRegressionWithLBFGS's default parameters consistent in Scala and Python	2016-02-29 00:55:51 -08:00
pom.xml	[SPARK-6363][BUILD] Make Scala 2.11 the default Scala version	2016-01-30 00:20:28 -08:00