[jira] [Resolved] (SPARK-23166) Add maxDF Parameter to CountVectorizer

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-23166?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-23166.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 2.4.0

Issue resolved by pull request 20367
[https://github.com/apache/spark/pull/20367]

> Add maxDF Parameter to CountVectorizer
> --------------------------------------
>
>                 Key: SPARK-23166
>                 URL: https://issues.apache.org/jira/browse/SPARK-23166
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.2.1
>            Reporter: Yacine Mazari
>            Assignee: Yacine Mazari
>            Priority: Minor
>             Fix For: 2.4.0
>
>
> Currently, the {{CountVectorizer}} has a {{minDF}} parameter.
> It might be useful to also have a {{maxDF}} parameter.
> It will be used as a threshold for filtering all the terms that occur very frequently in a text corpus, because they are not very informative or could even be stop-words.
> This is analogous to scikit-learn, [CountVectorizer|http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html], max_df.



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