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Selecting multiple partitions #3

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Peder2911 opened this issue Nov 24, 2021 · 4 comments
Open

Selecting multiple partitions #3

Peder2911 opened this issue Nov 24, 2021 · 4 comments
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enhancement New feature or request

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@Peder2911
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There are cases where it would be useful to select multiple partitions at once, combining them into a single output. For example, if one would like to train with both the test and train partitions to do holdout evaluation:

A suggested syntax is:

partitioner = DataPartitioner({"A":{"train":(1,10),"test":(11,20),"holdout":(21,30)}})

train_and_test = partitioner("A", ("train", "test"))
@Peder2911 Peder2911 added the enhancement New feature or request label Nov 24, 2021
@Peder2911 Peder2911 self-assigned this Nov 24, 2021
@hhegre
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hhegre commented Nov 24, 2021

Should this be discussed in conjunction with syntax for partitioning across units (cross-validation) rather than across times?

@Peder2911
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No, this only relates to time-partitioning.

@hhegre
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hhegre commented Nov 27, 2021

I might not have been clear. We need syntax for CV partition that follows the same logic. It might be useful to think of these two usages simultaneously? This type of combination across partitions could be useful also for CV.

@Peder2911
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Sure, but unit partitioning doesn't have the same implementation, even though it might seem similar. I'd open a separate issue for unit partitioning, mentioning that it should have the same kind of partitioning features as time-partitioning.

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