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Posted to issues@spark.apache.org by "Antonio Murgia (JIRA)" <ji...@apache.org> on 2015/08/19 05:09:45 UTC

[jira] [Created] (SPARK-10105) Adding most k frequent words parameter to Word2Vec implementation

Antonio Murgia created SPARK-10105:
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             Summary: Adding most k frequent words parameter to Word2Vec implementation
                 Key: SPARK-10105
                 URL: https://issues.apache.org/jira/browse/SPARK-10105
             Project: Spark
          Issue Type: Improvement
          Components: MLlib
            Reporter: Antonio Murgia
            Priority: Minor


When training Word2Vec on a really big dataset, it's really hard to evaluate the right minCount parameter, it would really help having a parameter to choose how many words you want to be in the vocabulary.
Furthermore, the original Word2Vec paper, state that they took into account the first 30k words.
 



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