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https://issues.apache.org/jira/browse/SPARK-19668?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15876080#comment-15876080
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Jacek KK commented on SPARK-19668:
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That's how i have it implemented in my project (by setting lowN and highN
variables), but I don't have any idea how to make it consistent (and
compatible) with current solution.
> Multiple NGram sizes
> --------------------
>
> Key: SPARK-19668
> URL: https://issues.apache.org/jira/browse/SPARK-19668
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.1.0
> Reporter: Jacek KK
> Priority: Minor
> Labels: beginner, easyfix, newbie
>
> It would be nice to have a possibility of specyfing the range (or maybe a
> list of) sizes of ngrams, like it is done in sklearn, as in
> http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html#sklearn.feature_extraction.text.TfidfVectorizer
> This shouldn't be difficult to add, the code is very straightforward, and I
> can implement it. The only issue is with the NGram API - should it just
> accept a number/tuple/list?
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