[scikit-learn] DBSCAN Border Points
Joel Nothman
joel.nothman at gmail.com
Tue Jan 30 18:17:01 EST 2018
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.shanehsazzadeh at 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 at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20180131/c37f9e69/attachment.html>
More information about the scikit-learn
mailing list