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

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-23166?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16335983#comment-16335983 ] 

Apache Spark commented on SPARK-23166:
--------------------------------------

User 'mgaido91' has created a pull request for this issue:
https://github.com/apache/spark/pull/20364

> 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
>            Priority: Minor
>
> 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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