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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-19668) Multiple NGram sizes
Date Sat, 04 Nov 2017 13:32:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-19668:
------------------------------------

    Assignee:     (was: Apache Spark)

> 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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