[jira] [Resolved] (SPARK-8455) Implement N-Gram Feature Transformer

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-8455?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-8455.
--------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.5.0

Issue resolved by pull request 6887
[https://github.com/apache/spark/pull/6887]

> 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
>            Assignee: Feynman Liang
>            Priority: Minor
>             Fix For: 1.5.0
>
>
> 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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