yuhao yang created SPARK-16592:
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Summary: Improving ml.Logistic Regression on speed and scalability
Key: SPARK-16592
URL: https://issues.apache.org/jira/browse/SPARK-16592
Project: Spark
Issue Type: Improvement
Components: ML
Reporter: yuhao yang
With the spreading application of Apache Spark* logistic regression, we've seen
more and more requirements come up about improving the speed and scalability.
Many suggestions and discussions have been evolving in the developer and user
communities. While it may be difficult to find an optimization for all the
cases, understanding the various scenarios and approaches will be important.
As discussed with [~josephkb], this JIRA is created for discussion and
collecting efforts on the optimization work of LR (logistic regression). All
the ongoing related JIRA will be linked here, as well as new ideas and
possibilities.
Users are encouraged to share their experiences/expectations on LR and track
the development status from the community. Developers can leverage the JIRA to
browse existing efforts, make communication and introduce research/development
resources.
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