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https://issues.apache.org/jira/browse/SPARK-2309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14951744#comment-14951744
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Sean Owen commented on SPARK-2309:
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Yeah, I also don't get it. In multinomial LR you still have the same features
for every output class. The slide you show just shows a loss function computed
over the loss for each of the N classes, not just 1. But the features are the
same. Implicitly, if an example is in class k then it's not in the other
classes.
> Generalize the binary logistic regression into multinomial logistic regression
> ------------------------------------------------------------------------------
>
> Key: SPARK-2309
> URL: https://issues.apache.org/jira/browse/SPARK-2309
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: DB Tsai
> Assignee: DB Tsai
> Priority: Critical
> Fix For: 1.3.0
>
>
> Currently, there is no multi-class classifier in mllib. Logistic regression
> can be extended to multinomial one straightforwardly.
> The following formula will be implemented.
> http://www.slideshare.net/dbtsai/2014-0620-mlor-36132297/25
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