Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/3000#issuecomment-61168626
Good point; I intended this to be used for labels too, so I'll add fit()
and transform() methods which take RDD[Double]. Perhaps I should relabel
"features" to "columns." I'd imagine someone either using 2 indexers (1 for
labels and 1 for features), or zipping the labels and features into 1 vector
and then using 1 indexer. We could also add other fit() and transform()
methods later on to prevent users from having to do the zipping manually.
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