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https://issues.apache.org/jira/browse/SOLR-3700?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13431873#comment-13431873
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Robert Muir commented on SOLR-3700:
-----------------------------------
in trainVocabulary:
{code}
TopDocs topDocs = indexSearcher.search(new MatchAllDocsQuery(),
Integer.MAX_VALUE);
{code}
Thats gonna be really slow if the goal is simply to iterate over all documents.
I would just grab indexSearcher.getIndexReader() and loop until maxDoc(), rather
than scoring in a massive priority queue.
in tokenizeDoc:
{code}
TokenStream tokenStream = analyzer.tokenStream(textFieldName, new
StringReader(doc));
while (tokenStream.incrementToken()) {
CharTermAttribute charTermAttribute =
tokenStream.getAttribute(CharTermAttribute.class);
result.add(charTermAttribute.toString());
}
{code}
this should use the mandatory reset() etc methods, otherwise its not safe, so
something like:
{code}
TokenStream tokenStream = analyzer.tokenStream(textFieldName, new
StringReader(doc));
CharTermAttribute charTermAttribute =
tokenStream.addAttribute(CharTermAttribute.class);
tokenStream.reset();
while (tokenStream.incrementToken()) {
result.add(charTermAttribute.toString());
}
tokenStream.end();
tokenStream.close();
{code}
If you change the test's analyzer from WhitespaceTokenizerFactory to
MockTokenizerFactory,
it should check for these things and currently fail, so thats an easy way to
test :)
> Create a Classification component
> ---------------------------------
>
> Key: SOLR-3700
> URL: https://issues.apache.org/jira/browse/SOLR-3700
> Project: Solr
> Issue Type: New Feature
> Reporter: Tommaso Teofili
> Priority: Minor
> Attachments: 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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