Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/216#issuecomment-38727471
@LIDIAgroup For the second item, it is very common to have different
training and descretizing data. For example, we have a labeled dataset
containing a subset of members, and we want to train a model based on it and
make predictions for other members. A discretizer is trained from the labeled
dataset, and then a predictive model is trained using the discretized features.
The next step is to make predictions, where we have to apply the same
discretization to other member feature vectors.
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