Closed ericphanson closed 3 years ago
@palday said:
I don't like DataPartitions for some reason. Are there other relevant uses of "partition" that we don't want to clobber by taking this name?
Also, soon we'll have KnapsackProblems.jl.
Are there other relevant uses of "partition" that we don't want to clobber by taking this name?
Hm, yeah. I think Partitions.jl
or Partitioning.jl
might be a bit too grand, esp for a package in General where there could be bigger projects wanting that name.
There's graph partitioning which I think is actually related but formulated differently.
DataPartitions might be a little too scoped to ML stuff; I think it's kind of nice if this package is written a bit generically, since this kind of problem comes up in other contexts too, and we might get contributors from a broader set of fields that way.
IntegerSplits
?
Is the existing name inaccurate?
assuming it is accurate, I kinda like the existing name (because it's precise/googleable), even if it's long
@jrevels I personally would say that the existing name is accurate. In fact it is nodding to the problem of the same name https://en.wikipedia.org/wiki/Multiway_number_partitioning
This package finds a solution to this problem, and is currently being applied internally at Beacon to find a nice configuration for a problem we face that is an instance of the Multiway Number Partitioning problem.
The context for the renaming is that we thought we might want to expand the scope beyond strictly the multiway partitioning problem-- that problem is the first bullet of https://github.com/beacon-biosignals/MultiwayNumberPartitioning.jl/issues/2#issue-972895738, but the others are kinda generalizations of it.
edit: but that doesn't mean we have to rename it, it could be implicitly MultiwayNumberPartitioning + generalizations thereof. Just wanted to say why we were talking about renaming it.
Ok let's just keep the name 😄
@palday @kimlaberinto any bikeshedding on the naming? Scope is to provide exact or approximate solutions to combinatorial problems around partitioning objects, with an eye to usage in cross validation and test/train splits in ML tasks. Things like:
name ideas:
Related work: