Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/8314#issuecomment-152986524
@yinxusen I'm trying to help debug the test failure in `Word2VecSuite`
added in
https://github.com/apache/spark/commit/c9d530e2e5123dbd4fd13fc487c890d6076b24bf#diff-a081b952fe8b6e09a492ef37e157b456
I find that changing the seed at all makes the result quite different and the
test fails. However the expected value is computed in a pretty clear way; I'm
trying to figure out why a particular seed is required here. Are the word
vectors chosen to work for the default seed of 42?
While looking at it I think we can fix one small thing in
`org.apache.spark.mllib.feature.Word2Vec`. The initial random vector (which is
what the seed affects) is not quite chosen uniformly:
```
Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() -
0.5f) / vectorSize)
```
should be more like
```
Array.fill[Float](vocabSize *
vectorSize)((initRandom.nextGaussian().toFloat) / vectorSize)
```
This isn't really the issue but something we could adjust. Of course this
also makes the test fail.
If we can't figure this out... I think we could hard-code this test to work
with the new seed behavior, on the theory that it's probably a test issue.
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