[scikit-learn] Questions on computation precision of DBSCAN

Mingzhe Hu mh4116 at columbia.edu
Wed Apr 27 14:24:32 EDT 2022

Dear community,

When I am calling the `sklearn.cluster.DBSCAN` function, I found it may
result in huge memory costs... I am trying to reduce the computation cost
by having my input data type as np.float16 and using "precomputed" as my
metric. But I found that it still uses float64 (as it returns me with some
errors like float64 computation leads to memory allocation failure) during
computation when `fit_predict` is called. All suggestions for reducing
computation costs are highly appreciated. Thanks.

All the best,
Mingzhe HU
Columbia University in the City of New York
M.S. in Electrical Engineering
mingzhe.hu at columbia.edu <mh4116 at columbia.edu>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mail.python.org/pipermail/scikit-learn/attachments/20220427/ccc95d0c/attachment.html>

More information about the scikit-learn mailing list