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https://issues.apache.org/jira/browse/LUCENE-4345?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13452980#comment-13452980
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Tommaso Teofili commented on LUCENE-4345:
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Thanks Lance for your useful insights, I'll definitely have a look :) .
bq. If you use index data which is already analyzed with the same analyzer as
your test (unseen) documents, you can use a lot more documents as input. More
is better. As the training data increases, signal drives out noise.
I agree, we could leverage this for sure.
bq. Once you add the ability to store & load models, training speed becomes
less important.
Regarding storing and loading models, the base intuition (at least my intuition
:P) in the case of Lucene is that the index itself plays that role.
> Create a Classification module
> ------------------------------
>
> Key: LUCENE-4345
> URL: https://issues.apache.org/jira/browse/LUCENE-4345
> Project: Lucene - Core
> Issue Type: New Feature
> Reporter: Tommaso Teofili
> Assignee: Tommaso Teofili
> Priority: Minor
> Attachments: LUCENE-4345_2.patch, LUCENE-4345.patch,
> SOLR-3700_2.patch, SOLR-3700.patch
>
>
> Lucene/Solr can host huge sets of documents containing lots of information in
> fields so that these can be used as training examples (w/ features) in order
> to very quickly create classifiers algorithms to use on new documents and /
> or to provide an additional service.
> So the idea is to create a contrib module (called 'classification') to host a
> ClassificationComponent that will use already seen data (the indexed
> documents / fields) to classify new documents / text fragments.
> The first version will contain a (simplistic) Lucene based Naive Bayes
> classifier but more implementations should be added in the future.
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