Bayes/CBayes classification on a non-existing feature
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Key: MAHOUT-826
URL: https://issues.apache.org/jira/browse/MAHOUT-826
Project: Mahout
Issue Type: Bug
Components: Classification
Affects Versions: 0.5
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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