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https://issues.apache.org/jira/browse/MADLIB-1178?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan updated MADLIB-1178:
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Description:
In the course of doing this story
https://issues.apache.org/jira/browse/MADLIB-1173
it was observed that handling large feature vectors could be done more
efficiently.
Story
As a MADlib developer
I want to improve the performance of DT/RF with large feature vectors
So that run-times are faster
Acceptance
1) Run performance tests with feature vectors > 1600 and compare run-times with
and without this story's improvements.
was:
Follow on from
https://issues.apache.org/jira/browse/MADLIB-1173
Story
As a MADlib developer
I want to improve the performance of DT/RF with large feature vectors
So that run-times are faster
Acceptance
1) Run performance tests with feature vectors > 1600 and compare run-times with
and without this story's improvements.
> Improve performance of DT/RF with large feature vectors
> -------------------------------------------------------
>
> Key: MADLIB-1178
> URL: https://issues.apache.org/jira/browse/MADLIB-1178
> Project: Apache MADlib
> Issue Type: Improvement
> Components: Module: Decision Tree
> Reporter: Frank McQuillan
> Fix For: v2.0
>
>
> In the course of doing this story
> https://issues.apache.org/jira/browse/MADLIB-1173
> it was observed that handling large feature vectors could be done more
> efficiently.
> Story
> As a MADlib developer
> I want to improve the performance of DT/RF with large feature vectors
> So that run-times are faster
> Acceptance
> 1) Run performance tests with feature vectors > 1600 and compare run-times
> with and without this story's improvements.
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