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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