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This allows fitting a (random) subset of the data on any partial_fit calls. This class fulfills the 'dataset subsampling' use case mentioned on page 10 of the Hyperband of the Hyperband paper (https://arxiv.org/pdf/1603.06560.pdf).
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What does this PR implement?
This allows for Hyperband to work with any estimator, not only those that implement
partial_fit. It does this by fitting a (random) subset of the data passed topartial_fit.This makes sense when computationally constrained, not memory constrained. I would expect this class to be used with Hyperband (or other adaptive searches) when computationally constrained, not memory constrained.
A good use-case for this is finding the hyper-parameters for embedding data into a low-dimensional space. This tends to be computationally expensive with moderate data and has many hyper-parameters (and they matter; see "Using t-SNE effectively").
Related work
This is based off the documentation re-organization in dask#221.
TODO