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Posted to dev@mahout.apache.org by "tom pierce (Created) (JIRA)" <ji...@apache.org> on 2011/12/03 02:41:40 UTC
[jira] [Created] (MAHOUT-911) Naive Bayes trains models that are
too large to apply
Naive Bayes trains models that are too large to apply
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Key: MAHOUT-911
URL: https://issues.apache.org/jira/browse/MAHOUT-911
Project: Mahout
Issue Type: Bug
Components: Classification
Affects Versions: 0.6
Reporter: tom pierce
I'm seeing the same issue that Lyall Morrison mentioned on the user list not too long ago; I can train a model that apparently has too many classes (or is otherwise too large) to read back in and apply to new documents.
I was able to duplicate this issue using the Wikipedia classification example. I used an expanded set of categories (125, which is well over the 30-some that caused trouble for Lyall).
I'll attach the list of categories I used.
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[jira] [Resolved] (MAHOUT-911) Naive Bayes trains models that are
too large to apply
Posted by "Robin Anil (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/MAHOUT-911?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Robin Anil resolved MAHOUT-911.
-------------------------------
Resolution: Fixed
Fix Version/s: 0.7
Assignee: Robin Anil
There is a new naive bayes implementation which has compact models based on mahout vectors, should be able to scale to wikipedia. The old version is deleted in the new release. I am marking this as resolved. Please reopen if you find any issues with that
> Naive Bayes trains models that are too large to apply
> -----------------------------------------------------
>
> Key: MAHOUT-911
> URL: https://issues.apache.org/jira/browse/MAHOUT-911
> Project: Mahout
> Issue Type: Bug
> Components: Classification
> Affects Versions: 0.6
> Reporter: tom pierce
> Assignee: Robin Anil
> Fix For: 0.7
>
> Attachments: example.wiki.categories.txt
>
>
> I'm seeing the same issue that Lyall Morrison mentioned on the user list not too long ago; I can train a model that apparently has too many classes (or is otherwise too large) to read back in and apply to new documents.
> I was able to duplicate this issue using the Wikipedia classification example. I used an expanded set of categories (125, which is well over the 30-some that caused trouble for Lyall).
> I'll attach the list of categories I used.
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[jira] [Updated] (MAHOUT-911) Naive Bayes trains models that are
too large to apply
Posted by "tom pierce (Updated) (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/MAHOUT-911?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
tom pierce updated MAHOUT-911:
------------------------------
Attachment: example.wiki.categories.txt
> Naive Bayes trains models that are too large to apply
> -----------------------------------------------------
>
> Key: MAHOUT-911
> URL: https://issues.apache.org/jira/browse/MAHOUT-911
> Project: Mahout
> Issue Type: Bug
> Components: Classification
> Affects Versions: 0.6
> Reporter: tom pierce
> Attachments: example.wiki.categories.txt
>
>
> I'm seeing the same issue that Lyall Morrison mentioned on the user list not too long ago; I can train a model that apparently has too many classes (or is otherwise too large) to read back in and apply to new documents.
> I was able to duplicate this issue using the Wikipedia classification example. I used an expanded set of categories (125, which is well over the 30-some that caused trouble for Lyall).
> I'll attach the list of categories I used.
--
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