Open atheyers opened 5 years ago
thanks! Looping wouldn't work, as we need to ensure all the samples have same dimensionality, but updating all samples at once can work.
For example, for an MLDataset
of tow samples id1
and id2
, it can be something like this:
ds.add_feature(name='first', dict(id1=1, id2=0))
ds.add_feature(name='second', dict(id1=2, id2=3))
ds.del_feature(name='first')
ds.update_feature(name='second', dict(id1=5, id2=9))
It would be nice to be able to loop through the list of subject IDs and make updates to the array of features stored under there, instead of having to create a new datastructure for small changes.