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@mengxr made the requested changes. I found it simpler to keep
`numFeatures` in combination with an array of offsets instead of just the
cumulative count though.
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--- Diff:
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LGTM except minor comments.
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Merged into master. Thanks!
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Github user ericl commented on the pull request:
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@mengxr I did the refactoring as suggested
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Github user mengxr commented on the pull request:
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Had an offline discussion with @ericl
* split this PR into two
1. an `Interaction` transformer that only handles ML columns (`Double`
and `Vector` with
Github user dputler commented on the pull request:
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I'm not clear as to how the order operation is determined. Looking at the
tests, in the case of a categorical interaction it appears that it is based on
the order in
Github user mengxr commented on the pull request:
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@dputler Under distributed setting, we need to make at least one pass to
collect all categories. The ordering is not alphabetical but by frequency
Github user dputler commented on the pull request:
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That actually doesn't deal with the scoring issue. What happens when new
data to be predicted from an existing model has a more frequent category in a
categorical
Github user dputler commented on the pull request:
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Thanks Eric, I knew that was it really wasn't an issue related to this
specific pull request, but one that exposed an issue that, from past
experience, looked like
Github user ericl commented on the pull request:
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If if I understand correctly, the concern is that the category to index
assignment when predicting data will be different from that used when fitting
the model. This
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@mengxr done, this PR now just has the RInteraction changes.
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