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https://issues.apache.org/jira/browse/SPARK-17718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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DB Tsai resolved SPARK-17718.
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Resolution: Fixed
Fix Version/s: 2.1.0
> Make loss function formulation label note clearer in MLlib docs
> ---------------------------------------------------------------
>
> Key: SPARK-17718
> URL: https://issues.apache.org/jira/browse/SPARK-17718
> Project: Spark
> Issue Type: Documentation
> Reporter: Tobi Bosede
> Assignee: Sean Owen
> Priority: Trivial
> Fix For: 2.1.0
>
>
> https://spark.apache.org/docs/1.6.0/mllib-linear-methods.html#mjx-eqn-eqregPrimal
> The loss function here for logistic regression is confusing. It seems to
> imply that spark uses only -1 and 1 class labels. However it uses 0,1. Note
> below needs to make this point more visible to avoid confusion.
> "Note that, in the mathematical formulation in this guide, a binary label
> y is denoted as either +1 (positive) or −1 (negative), which is convenient
> for the formulation. However, the negative label is represented by 0 in
> spark.mllib instead of −1, to be consistent with multiclass labeling."
> Better yet, the loss function should be replaced with that for 0, 1 despite
> mathematical inconvenience, since that is what is actually implemented.
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