[jira] [Updated] (MADLIB-1095) Use populated parts of feature vector even if it contains one or more NULL entries

["Frank McQuillan (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MADLIB-1095?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Frank McQuillan updated MADLIB-1095:
------------------------------------
    Fix Version/s:     (was: v1.12)
                   v1.11

> Use populated parts of feature vector even if it contains one or more NULL entries
> ----------------------------------------------------------------------------------
>
>                 Key: MADLIB-1095
>                 URL: https://issues.apache.org/jira/browse/MADLIB-1095
>             Project: Apache MADlib
>          Issue Type: Improvement
>          Components: Module: Decision Tree
>            Reporter: Frank McQuillan
>             Fix For: v1.11
>
>
> Context 
> Currently in DT/RF if the feature vector contains any NULLs, the whole row will be ignored in the training data.  This is not ideal, especially in the case where training data is sparse.
> Story
> As a data scientist, I want the DT/RF modules to use the non-NULL parts of the feature vector, and not discard the whole row, so that I can get better accuracy for classification/regression in the case of sparse data.
> Acceptance
> TBD



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