On 11/21/18 10:34 AM, Gael Varoquaux wrote:
Joris has just accepted to help with benchmarking. We can have
preliminary results earlier. The question really is: out of the different
variants that exist, which one should we choose. I think that it is a
legitimate question that arises on many of our PRs.
Thanks Joris! I could also ask Jan to help ;)
The question for this particular issue for me is also "what are good
benchmark datasets".
It's a somewhat different task than what you're benchmarking with dirty
cat, right?
In dirty cat you used dirty categories, which is a subset of all
high-cardinality categorical
variables.
Whether "clean" high cardinality variables like zip-codes or dirty ones
are the better
benchmark is a bit unclear to me, and I'm not aware of a wealth of
datasets for either :-/
But in general, I don't think that we should rush things because of
deadlines. Consequences of a rush are that we need to change things after
merge, which is more work. I know that it is slow, but we are quite a
central package.
I agree.
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