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https://issues.apache.org/jira/browse/SPARK-2309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14952869#comment-14952869
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christian sommeregger commented on SPARK-2309:
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Sorry everyone! I got confused by the different terminologies out there. (the
model on slideshare is of course implemented correctly)
I was talking about a conditional multinomial logit:
So instead of
U_is=X_s*w_i
( U_is denotes the utility of item i in choice situation s, features X_s are
constant across alternatives, weights w_i are
item specific)
we would use:
U_is=X_si*w
(weights are the same across alternatives, but features can be distinct for
each item, and can be different for each s)
(check 6.3.3. in http://data.princeton.edu/wws509/notes/c6s3.html)
I would be happy to contribute some code. Do you think this would be an
interesting extension. Should I create a new ticket for this ?
> 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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