[jira] [Commented] (SPARK-16149) API consistency discussion: CountVectorizer.{minDF -> minDocFreq, minTF -> minTermFreq}

["yuhao yang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-16149?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15345736#comment-15345736 ] 

yuhao yang commented on SPARK-16149:
------------------------------------

For the general guideline, I would vote for consistency with existing API in MLlib. It only brings confusion to users if we use different names for similar parameters in different algorithms.
For this specific issue here, we can perhaps deprecate the current minTF/minDF and add new API for minTermFreq/minDocFreq.


> API consistency discussion: CountVectorizer.{minDF -> minDocFreq, minTF -> minTermFreq}
> ---------------------------------------------------------------------------------------
>
>                 Key: SPARK-16149
>                 URL: https://issues.apache.org/jira/browse/SPARK-16149
>             Project: Spark
>          Issue Type: Brainstorming
>          Components: MLlib
>    Affects Versions: 2.0.0
>            Reporter: Xiangrui Meng
>
> We used `minDF` and `minTF` in CountVectorizer and `minDocFreq` in IDF. It would be nice to keep the naming consistent. This was discussed in https://github.com/apache/spark/pull/7388 and the decision was made based on sklearn compatibility. However, we didn't look broadly across MLlib APIs. Maybe we can live with this small inconsistency but it would be nice to discuss the guideline (consistent with other libraries or existing ones in MLlib).
> cc: [~josephkb] [~yuhaoyan]



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