Hi,
I'm trying to use LSH Forest approximate neighbor search method to obtain
radius neighbors in DBSCAN. It adheres the API of sklearn.neighbors (at
least radius_neighbors method at this moment). But LSH Forest itself has a
set of parameters, so they need to be initialized.
I'm thinking about passing an argumant to DBSCAN init method as
`approximate_neighbors=True` (or something suitable) and have the LSH
Forest parameters as well in DBSCAN init method.
The other method Robert suggested to subclass from DBSCAN to use
approximate neighbors.
Once LSH Forest is initialized, it's just a matter of applying that in the
place of `NearestNeighbors`. Are the above methods appropriate or is there
better ways?
PR to LSH Forest: https://github.com/scikit-learn/scikit-learn/pull/3304
Best Regards,
Maheshakya
--
Undergraduate,
Department of Computer Science and Engineering,
Faculty of Engineering.
University of Moratuwa,
Sri Lanka
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