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From "Robin Anil (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAHOUT-487) Issues with memory use and inconsistent or state-influenced results when using CBayesAlgorithm
Date Tue, 20 Nov 2012 17:50:58 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-487?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13501332#comment-13501332
] 

Robin Anil commented on MAHOUT-487:
-----------------------------------

This package no longer exists, try using the new re-implementation.
                
> 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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