[jira] [Resolved] (SPARK-6349) Add probability estimates in SVMModel predict result

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-6349?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-6349.
------------------------------
    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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