You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Thank you for a very cool library. I have a quick question. Maybe I missed something, but right now there are no way to retrieve the original index of the samples in the subset to identify which samples/row number the algorithm chose? This need comes up in 2 scenarios:
When I want to know whether I have sufficiently covered my data distribution based on UMAP 2D embedding, I need to know the index of the samples in the subset to merge it back with the UMAP representation
When I have features [A, B, C], but only want to perform submodular optimization on features [A, B], and then want to know the values of feature C of all the samples in the subset.
Right now I don't see any way to extract out the index/numpy array row number of the chosen samples.
The text was updated successfully, but these errors were encountered:
Hi Jacob,
Thank you for a very cool library. I have a quick question. Maybe I missed something, but right now there are no way to retrieve the original index of the samples in the subset to identify which samples/row number the algorithm chose? This need comes up in 2 scenarios:
When I want to know whether I have sufficiently covered my data distribution based on UMAP 2D embedding, I need to know the index of the samples in the subset to merge it back with the UMAP representation
When I have features [A, B, C], but only want to perform submodular optimization on features [A, B], and then want to know the values of feature C of all the samples in the subset.
Right now I don't see any way to extract out the index/numpy array row number of the chosen samples.
The text was updated successfully, but these errors were encountered: