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https://issues.apache.org/jira/browse/SPARK-12153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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YongGang Cao updated SPARK-12153:
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Description:
sentence boundary matters for sliding window, we shouldn't train model from a
window across sentences. the current 100 word as a hard split for sentences
doesn't really make sense.
And the cosinesimilarity functions is private which is useless for caller.
we may need to access the vocabulary and wordindex table as well, those need
getters
I made changes to address above issues.
here is the pull request: https://github.com/apache/spark/pull/10152
was:
sentence boundary matters for sliding window, we shouldn't train model from a
window across sentences. the current 100 word as a hard split for sentences
doesn't really make sense.
And the cosinesimilarity functions is private which is useless for caller.
we may need to access the vocabulary and wordindex table as well, those need
getters
I made changes to address above issues. will send out pull request for your
review.
> Word2Vec uses a fixed length for sentences which is not reasonable for
> reality, and similarity functions and fields are not accessible
> --------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-12153
> URL: https://issues.apache.org/jira/browse/SPARK-12153
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.5.2
> Reporter: YongGang Cao
> Priority: Minor
> Labels: patch
>
> sentence boundary matters for sliding window, we shouldn't train model from a
> window across sentences. the current 100 word as a hard split for sentences
> doesn't really make sense.
> And the cosinesimilarity functions is private which is useless for caller.
> we may need to access the vocabulary and wordindex table as well, those need
> getters
> I made changes to address above issues.
> here is the pull request: https://github.com/apache/spark/pull/10152
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