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https://issues.apache.org/jira/browse/MAHOUT-688?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13030477#comment-13030477
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Vasil Vasilev commented on MAHOUT-688:
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Hi Grant,
Thanks for contributing to the code. One remark from my side: In fact the
standard deviation was intentionally calculated in such a way, because I wanted
to "force" a zero mean. I.e. I want to calculate the standard deviation in such
a way that the words with document frequency (DF) near to the zero have highest
probability of getting in. I.e. I imagine that for every word DF there is a -DF
(DF with the opposite sign) and calculate the standard deviation in such a way.
This ensures that only high DF words will be pruned.
Regards, Vasil
> High Document Frequency pruning for seq2sparse
> ----------------------------------------------
>
> Key: MAHOUT-688
> URL: https://issues.apache.org/jira/browse/MAHOUT-688
> Project: Mahout
> Issue Type: Improvement
> Reporter: Vasil Vasilev
> Assignee: Grant Ingersoll
> Priority: Minor
> Labels: Vectorization
> Fix For: 0.6
>
> Attachments: MAHOUT-688.patch, MAHOUT-688.patch
>
>
> This improvement allows to prune the words with high document frequencies
> from the tf and tf-idf vectors produced by seq2sparse, based on the standard
> deviation of the words' document frequencies and specifying which rods to be
> pruned in a means of times this standard deviation. One good option is 3
> times the standard deviation
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