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https://issues.apache.org/jira/browse/SPARK-9834?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14734170#comment-14734170
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Debasish Das commented on SPARK-9834:
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If you are open to use breeze.proximal.QuadraticMinimizer we can support
elastic net in this variant as well...I can add it on top of your PR...it will
be very similar to quadraticminimizer integration to ALS...I have done runtime
benchmarks compared to OWLQN and if we can afford to do dense cholesky
QuadraticMinimizer converges faster than OWLQN...there are two new features I
am working on...sparse ldl through tim davis lgpl code and using breeze sparse
matrix for sparse gram and conic formulations and admm acceleration using
nesterov method...admm can also be run in the same complexity as FISTA...david
goldferb proved it.
> Normal equation solver for ordinary least squares
> -------------------------------------------------
>
> Key: SPARK-9834
> URL: https://issues.apache.org/jira/browse/SPARK-9834
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
>
> Add normal equation solver for ordinary least squares with not many features.
> The approach requires one pass to collect AtA and Atb, then solve the problem
> on driver. It works well when the problem is not very ill-conditioned and not
> having many columns. It also provides R-like summary statistics.
> We can hide this implementation under LinearRegression. It is triggered when
> there are no more than, e.g., 4096 features.
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