Hi, That is interesting. Would you please share some code on how you are setting the regularization type, regularization parameters and running Logistic Regression?
Thanks, Burak ----- Original Message ----- From: "SK" <skrishna...@gmail.com> To: u...@spark.incubator.apache.org Sent: Wednesday, August 6, 2014 6:18:43 PM Subject: Regularization parameters Hi, I tried different regularization parameter values with Logistic Regression for binary classification of my dataset and would like to understand the following results: regType = L2, regParam = 0.0 , I am getting AUC = 0.80 and accuracy of 80% regType = L1, regParam = 0.0 , I am getting AUC = 0.80 and accuracy of 50% To calculate accuracy I am using 0.5 as threshold. prediction <0.5 is class 0, and prediction >= 0.5 is class 1. regParam = 0.0, implies I am not using any regularization, is that correct? If so, it should not matter whether I specify L1 or L2, I should get the same results. So why is the accuracy value different? thanks -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Regularization-parameters-tp11601.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
