[jira] [Updated] (MAHOUT-1391) Possibility to disable confusion matrix in naive bayes

["Sebastian Schelter (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-1391?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sebastian Schelter updated MAHOUT-1391:
---------------------------------------

    Resolution: Not a Problem
        Status: Resolved  (was: Patch Available)

If you have labels in your testset that are not in your trainingset, then your setup is flawed and you should not run that test.

> Possibility to disable confusion matrix in naive bayes
> ------------------------------------------------------
>
>                 Key: MAHOUT-1391
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1391
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Classification
>    Affects Versions: 0.8
>            Reporter: Mansur Iqbal
>             Fix For: 1.0
>
>         Attachments: MAHOUT-1391.patch
>
>
> Sometimes confusion matrix is to big and not really necessary.
> And there is another case for the possibility:
> If you split a dataset with many labels with random selection percent to testdataset and trainingdataset, it could happen, that there are classes/labels in testdata, which do not appear in the trainingdataset. By creating a model with the trainingdata the created labelindex does not include some labels from testdata. Therefore if you test on this model with the testdata, mahout tries to create a confusion matrix with the labels from testdata which are not included in the labelindex and throws an exception.



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