Github user avulanov commented on the issue:
https://github.com/apache/spark/pull/13617
@JeremyNixon Thank you for your PR! Actually, regression was in the
original Multilayer perceptron PR:
https://github.com/apache/spark/pull/7621/commits/a2261330c227be8ef26172dbe355a617d653553a.
However, we removed it after discussion with @mengxr. The reason is that
regression needs to have only one output to be consistent with
`RegressionModel` in Spark ML. We did not find an evidence that multilayer
perceptron with one output is widely used in research or in industry. We posted
a JIRA issue indicating that use cases are needed to justify the implementation
of this model https://issues.apache.org/jira/browse/SPARK-10409. There was no
discussion until now, and I am glad that we finally have it. I think we are
still missing some strong motivating use cases. Could you provide few
references to research papers or industrial applications that rely on MLP
regression?
The other way of addressing this problem would be to implement multilayer
perceptron regression with multiple outputs. Justifying its usefulness might be
simpler. We might need to implement multivariate regression interface
beforehand: https://issues.apache.org/jira/browse/SPARK-9120
+1 for separating the activation functions into another PR. Currently,
there is no public API to specify activation functions in hidden layers.
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