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https://issues.apache.org/jira/browse/MAHOUT-1621?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andrew Musselman resolved MAHOUT-1621.
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Resolution: Not a Problem
Closing, not sure what the goal was here.
> k-fold cross-validation in MapReduce Random Forest example?
> -----------------------------------------------------------
>
> Key: MAHOUT-1621
> URL: https://issues.apache.org/jira/browse/MAHOUT-1621
> Project: Mahout
> Issue Type: Question
> Components: Examples
> Environment: Ubuntu Linux 14.04
> Reporter: Tawfiq Hasanin
> Labels: legacy
> Fix For: 1.0
>
>
> My goal is to modify MapReduce Random Forest example by combining
> BuildForest.java and TestForest.java into a new class called RandomForest.java
> The main point is to input one data file which is going to be used in
> training and testing; with k-fold cross-validation.
> I have a big data with hight diminutional features and small amount of
> instances.
> Seems to be a frustrating dead-end. is this process achievable? Or is it
> against MapReduce nature?
> Thanks..
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