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

["Apache Spark (JIRA)" <ji...@apache.org>]

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

Apache Spark reassigned SPARK-8455:
-----------------------------------

    Assignee: Feynman Liang  (was: Apache Spark)

> 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
>
> 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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