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https://issues.apache.org/jira/browse/SPARK-6349?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-6349.
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Resolution: Won't Fix
> 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)
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