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https://issues.apache.org/jira/browse/MAHOUT-487?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved MAHOUT-487.
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Resolution: Won't Fix
Fix Version/s: (was: 0.6)
It looks like nobody's taking this up after a year, so marking it as WontFix
> Issues with memory use and inconsistent or state-influenced results when
> using CBayesAlgorithm
> ----------------------------------------------------------------------------------------------
>
> Key: MAHOUT-487
> URL: https://issues.apache.org/jira/browse/MAHOUT-487
> Project: Mahout
> Issue Type: Bug
> Components: Classification
> Affects Versions: 0.3, 0.4, 0.5
> Reporter: Drew Farris
> Assignee: Robin Anil
> Priority: Minor
>
> Came across this digging through the mailing list archives for something
> else, probably worth tracking as an issue.
> {quote}
> During classification, every word still unknown is added to
> featureDictionary. This leads to the excessive growth if lots of texts
> with unknown words are to be classified. The inconsistency is caused by
> using a "vocabCount" that is not reset after each classification.
> Indeed, featureDictionary.size() is used for "vocabCount", which
> increases every time new unknown words are discovered.
> {quote}
> See:
> http://www.lucidimagination.com/search/document/7dabe3efec8d136d/issues_with_memory_use_and_inconsistent_or_state_influenced_results_when_using_cbayesalgorit#8853165db260bf75
> Alternately per Robin:
> {quote}
> We can remove the addition features to the
> dictionary altogether. Will yield better performance, and lock down the
> model. Will require a bit more modification
> {quote}
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