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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