[jira] [Created] (SPARK-4494) IDFModel.transform() add support for single vectors

["Jean-Philippe Quemener (JIRA)" <ji...@apache.org>]

Jean-Philippe Quemener created SPARK-4494:
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             Summary: IDFModel.transform() add support for single vectors
                 Key: SPARK-4494
                 URL: https://issues.apache.org/jira/browse/SPARK-4494
             Project: Spark
          Issue Type: New Feature
          Components: MLlib
            Reporter: Jean-Philippe Quemener


For now when using the tfidf implementation in mllib you have no other possibility to map your data back onto i.e. labels or ids than use a hackish way with ziping: {quote} 1. Persist input RDD. 2. Transform it to just vectors and apply IDFModel 3. zip with original RDD 4. transform label and new vector to LabeledPoint{quote}

Source:[http://stackoverflow.com/questions/26897908/spark-mllib-tfidf-implementation-for-logisticregression]

I think as in production alot of users want to map their data back to some identifier, it would be a good imporvement to allow using single vectors on IDFModel.transform()



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