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Perhaps new class might NOT be necessary, if we let MLDataset.dtype be array of numpy.dtypes corresponding to each feature, and indicate it during init?
Or we can define a MixedDataset class which takes care of all the init and cfg, and makes it easy to handle fully generic mixed datatypes.
Gotta work it out, and test it.
The text was updated successfully, but these errors were encountered:
raamana
changed the title
New class: MixedDataset allowing for arbitrary data types for each sample
New class: MixedDataset allowing for arbitrary data types
Feb 6, 2019
Perhaps new class might NOT be necessary, if we let
MLDataset.dtype
be array ofnumpy.dtype
s corresponding to each feature, and indicate it duringinit
?Or we can define a
MixedDataset
class which takes care of all the init and cfg, and makes it easy to handle fully generic mixed datatypes.Gotta work it out, and test it.
The text was updated successfully, but these errors were encountered: