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Nick Pentreath commented on SPARK-6349: --------------------------------------- This is now covered by {{ml}}'s {{LinearSVC}}. Shall we close? > Add probability estimates in SVMModel predict result > ---------------------------------------------------- > > Key: SPARK-6349 > URL: https://issues.apache.org/jira/browse/SPARK-6349 > Project: Spark > Issue Type: New Feature > Components: MLlib > Affects Versions: 1.2.1 > Reporter: tanyinyan > Original Estimate: 168h > Remaining Estimate: 168h > > In SVMModel, predictPoint method output raw margin(threshold not set) or 1/0 > label(threshold set). > when SVM are used as a classifier, it's hard to find a good threshold,and the > raw margin is hard to understand. > when I am using SVM on > dataset(https://www.kaggle.com/c/avazu-ctr-prediction/data), train on the > first day's dataset(ignore field id/device_id/device_ip, all remaining fields > are concidered as categorical variable, and sparsed before SVM) and predict > on the same data with threshold cleared, the predict result are all > negative. I have to set threshold to -1 to get a reasonable confusion matrix. > So, I suggest to provide probability predict result in SVMModel as in > libSVM(Platt's binary SVM Probablistic Output) -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org