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https://issues.apache.org/jira/browse/MAHOUT-145?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12735703#action_12735703
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Deneche A. Hakim commented on MAHOUT-145:
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to be able to predict the class of an out-of-bag instance, one must classify it
using all the trees of the forest, and because each mapper has access to a
subset of the trees, a second job is needed. Unless of course I'm missing
something.
I already implemented the first job, now I should start on the second.
> PartialData mapreduce Random Forests
> ------------------------------------
>
> Key: MAHOUT-145
> URL: https://issues.apache.org/jira/browse/MAHOUT-145
> Project: Mahout
> Issue Type: New Feature
> Components: Classification
> Reporter: Deneche A. Hakim
> Priority: Minor
>
> This implementation is based on a suggestion by Ted:
> "modify the original algorithm to build multiple trees for different portions
> of the data. That loses some of the solidity of the original method, but
> could actually do better if the splits exposed non-stationary behavior."
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