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https://issues.apache.org/jira/browse/MADLIB-1092?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15979575#comment-15979575
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Frank McQuillan commented on MADLIB-1092:
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We used `row_num` (number of rows in a group) and `dimension` (the dimension of
the feature array i.e., independent column in elastic net). `row_num` will most
likely be different for groups, but we are currently assuming that the
`dimension` of the feature vector will remain the same across groups.
This is a reasonable assumption, unless someone thinks differently.
> Elastic Net gives inconsistent results with grouping
> ----------------------------------------------------
>
> Key: MADLIB-1092
> URL: https://issues.apache.org/jira/browse/MADLIB-1092
> Project: Apache MADlib
> Issue Type: Bug
> Components: Module: Regularized Regression
> Reporter: Nandish Jayaram
> Fix For: v1.11
>
>
> Elastic net train seems to be giving incorrect results when used with
> grouping.
> Steps:
> - Run elastic net (train) on a table and obtain a model (M1).
> - Create a new table with all rows in the original input table and assign
> group value 1 for it.
> - Replicate the rows in the table and assign group value 2 for the replicated
> rows.
> - Run the elastic net train function with grouping while keeping the same
> optimization parameters for the function.
> Result:
> - The model (for each group) when run with grouping is different from the
> model M1.
> - The model for both the groups is the same, but not same as M1.
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