[ https://issues.apache.org/jira/browse/SPARK-6080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14341426#comment-14341426 ]
Yanbo Liang commented on SPARK-6080: ------------------------------------ This bug is easy to reproduce. In a PySpark environment, when you call model = LogisticRegressionWithSGD.train(data, regType=None) it will return a LogisticRegressionModel which was trained with no regularization. But when you run model = LogisticRegressionWithLBFGS.train(data, regType=None) it will throw an exception java.lang.IllegalArgumentException: Invalid value for 'regType' parameter. Can only be initialized using the following string values: ['l1', 'l2', None]. This is due to when invoke callMLlibFunc at python/pyspark/mllib/classification.py, the parameter was assigned to "str(regType)" which translate None(Python) to "None"(Java/Scala). The right way should be translate None(Python) to null(Java/Scala). We need to do the same thing as LogisticRegressionWithSGD. > LogisticRegressionWithLBFGS in PySpark was assigned wrong "regType" parameter > ----------------------------------------------------------------------------- > > Key: SPARK-6080 > URL: https://issues.apache.org/jira/browse/SPARK-6080 > Project: Spark > Issue Type: Bug > Components: MLlib, PySpark > Reporter: Yanbo Liang > > Currently LogisticRegressionWithLBFGS in > python/pyspark/mllib/classification.py will invoke callMLlibFunc with a wrong > "regType" parameter. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org