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Sometimes, we may want to pass extra variables to be split (like heights or other numerical/categorical values) to be split by BlockKFold and BlockShuffleSplit (see fatiando/community#86). Right now, there are two things blocking this:
Description of the desired feature:
Sometimes, we may want to pass extra variables to be split (like heights or other numerical/categorical values) to be split by
BlockKFold
andBlockShuffleSplit
(see fatiando/community#86). Right now, there are two things blocking this:BaseBlockCrossValidator
checks for 2 dimensions onX
: https://github.com/fatiando/verde/blob/main/verde/base/base_classes.py#L81easting=X[:,0]
andnorthing=X[:,1]
: https://github.com/fatiando/verde/blob/main/verde/model_selection.py#L184A solution would be to:
coordinate_columns=[0, 1]
that specifies which columns of the feature matrixX
correspond to the coordinates.I think the rest should work and make these classes more usable to general spatial machine learning.
Are you willing to help implement and maintain this feature?
Maybe but I have no bandwidth for this right now and don't really have a use for it just yet. Happy for anyone else to give it a shot.
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