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thank you for a great package! I'm new to ID estimation, hence a very naive question that I'm sure would properly merit a complex answer: is it possible to provide recommendations on which algorithms to try first for which use cases? E.g., if I plan to use UMAP+HDBSCAN clustering subsequently (a rather common choice nowadays, I believe) and my dataset has 5000 samples with 1000 features each, is there a starting recommendation? I'm happy to read around; I just found it hard to find simple recommendations for practitioners. I believe some (any) such guidance could greatly increase the value of the package, even if recommendations are less than perfect.
Cheers,
Eike
The text was updated successfully, but these errors were encountered:
Hi,
thank you for a great package! I'm new to ID estimation, hence a very naive question that I'm sure would properly merit a complex answer: is it possible to provide recommendations on which algorithms to try first for which use cases? E.g., if I plan to use UMAP+HDBSCAN clustering subsequently (a rather common choice nowadays, I believe) and my dataset has 5000 samples with 1000 features each, is there a starting recommendation? I'm happy to read around; I just found it hard to find simple recommendations for practitioners. I believe some (any) such guidance could greatly increase the value of the package, even if recommendations are less than perfect.
Cheers,
Eike
The text was updated successfully, but these errors were encountered: