GitHub user tmnd1991 opened a pull request:
https://github.com/apache/spark/pull/8301
[SPARK-10105] Add most frequent k parameter to Word2Vec
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 most frequent 1M words.
When the mostFrequentK parameter is set, the minCount parameter is ignored.
In this way we'll end up with the most frequent k words in the vocabulary.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/tmnd1991/spark master
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/8301.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #8301
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commit d4534661e4e740cc0c306edf796e531b6ef66f4d
Author: Antonio Murgia <[email protected]>
Date: 2015-08-19T04:04:13Z
[SPARK-10105] Add most frequent k parameter to Word2Vec
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