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https://issues.apache.org/jira/browse/MAHOUT-826?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andre-Philippe Paquet updated MAHOUT-826:
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Status: Open (was: Patch Available)
> Bayes/CBayes classification on a non-existing feature
> -----------------------------------------------------
>
> Key: MAHOUT-826
> URL: https://issues.apache.org/jira/browse/MAHOUT-826
> Project: Mahout
> Issue Type: Bug
> Components: Classification
> Reporter: Andre-Philippe Paquet
> Priority: Minor
>
> (see http://comments.gmane.org/gmane.comp.apache.mahout.user/9597)
> Using CBayes or Bayes, when trying to classify a feature/word that doesn't
> exist in the model, instead of returning the default/unknown label, the
> algorithm returns all labels with a constant score (ex: 12.386649147018964).
> After a quick look in CBayesAlgorithm, I found the problem in the
> featureWeight function that returns the theta normalized weight even if the
> feature didn't have any match (result=0).
> As a fix, I overrided the function in a subclass and return 0 if the weight
> of the current feature in the current label is 0.
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