Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/3735#issuecomment-67553377
LGTM, pending Jenkins.
This kind of test seems pretty fragile anyways. I guess it provides a
check for optimization behavior changing underneath, but at some point, it
might be better to switch to better checks for convergence. E.g., we could use
a well-conditioned problem and compare the results after a bunch of iterations
from different starting points. The epsilon error allowed could be calculated
properly based on the convergenceTol + the objective. Is that too much for
now? It could be a JIRA instead.
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