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https://issues.apache.org/jira/browse/MAHOUT-955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Robin Anil updated MAHOUT-955:
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Fix Version/s: 0.7
> Bayes classification result are unstable after classifying non-existing
> features
> --------------------------------------------------------------------------------
>
> Key: MAHOUT-955
> URL: https://issues.apache.org/jira/browse/MAHOUT-955
> Project: Mahout
> Issue Type: Bug
> Components: Classification
> Affects Versions: 0.5
> Environment: JRE 7
> Reporter: Michał B
> Assignee: Robin Anil
> Priority: Critical
> Labels: Bayes,, InMemoryDatastore,, vocabCount
> Fix For: 0.7
>
>
> Bayes classification results are unstable, and change during runtime!
> Sample test:
> MyClassifier classifier = new MyClassifier(new BayesAlgorithm(),params);
> //Custom simple wrapper for classifier
> ClassifierResult category = classifier.classify("existing");
> double resultA = category.getScore();
> category = classifier.classify("nonexisting");
> category = classifier.classify("existing");
> double resultB = category.getScore();
> Assert.assertEquals(resultA,resultB,0.0); // FAIL!!!
> Test like the one above will fail. Because nonexisting tokens are added to
> InMemoryBayesDatastore->featureDictionary therefore
> datastore.getWeight("sumWeight", "vocabCount") change after classification of
> unknown feature. Moreover, the featureDictionary fills with not wanted
> strings using heapspace.
> More on this here
> http://www.lucidimagination.com/search/document/7dabe3efec8d136d/issues_with_memory_use_and_inconsistent_or_state_influenced_results_when_using_cbayesalgorit#8853165db260bf75
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