Github user avulanov commented on the pull request:
https://github.com/apache/spark/pull/8314#issuecomment-156208076
I was thinking about removing the stochastic part from the tests. However,
the issue is that I need to test that stochastic initialization of parameters
for machine learning does work, i.e. the optimization will converge with such
parameters. Could you suggest a better way of doing this as opposed to use the
seed?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
