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From Maandy <>
Subject [MLlib] Extensibility of MLlib classes (Word2VecModel etc.)
Date Wed, 09 Sep 2015 09:01:12 GMT

I'm trying to implement doc2vec
(, mainly for
sport/research purpose due to all it's limitations so I would probably not
even try to PR it into MLlib itself) but to do that it would be highly
useful to have access to MLlib's Word2VecModel class, which is mostly
private. Is there any reason (i.e. some Spark/MLlib guidelines) for that or
would it be ok to refactor the code and make a PR? I've found a similar JIRA
issue which was posted almost a year ago but for some reason it got closed:


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