[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>
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