It includes non-core points, but not points that are out of eps from any core point. You can modify eps and min_samples. But perhaps you should just choose a different clustering algorithm if this is behaviour you absolutely do not want.
On 30 January 2018 at 23:24, AMIR SHANEHSAZZADEH < amir.p.shanehsazza...@umasd.net> wrote: > Hello, > > I am working with the latest implementation of DBSCAN. I believe that > scikit-learn's implementation does not include non-core points in clusters. > This results in border points not being included in clusters. Is there any > way to remedy this issue so that border points are included in their > respective clusters? Do you know what modifications I would need to make > the code? > > Thank you, > Amir Shanehsazzadeh > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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