[jira] [Updated] (MAHOUT-1621) k-fold cross-validation in MapReduce Random Forest example?

["Andrew Palumbo (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-1621?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Palumbo updated MAHOUT-1621:
-----------------------------------
    Labels: legacy  (was: )

> 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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