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https://issues.apache.org/jira/browse/SPARK-8455?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Feynman Liang updated SPARK-8455:
---------------------------------
Description:
N-grams are a NLP feature representation which generalize bag of words to
include local context (the n-1 preceding words). We can implement N-grams in ML
as a feature transformer (likely directly after tokenization).
For example, "this is a test" should tokenize to ["this","is","a","test"],
which upon applying a 2-gram feature transform should yield
[["this","is"],["is","a"],["a","test"]].
> Implement N-Gram Feature Transformer
> ------------------------------------
>
> Key: SPARK-8455
> URL: https://issues.apache.org/jira/browse/SPARK-8455
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Feynman Liang
> Priority: Trivial
>
> N-grams are a NLP feature representation which generalize bag of words to
> include local context (the n-1 preceding words). We can implement N-grams in
> ML as a feature transformer (likely directly after tokenization).
> For example, "this is a test" should tokenize to ["this","is","a","test"],
> which upon applying a 2-gram feature transform should yield
> [["this","is"],["is","a"],["a","test"]].
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