[mlpack] Parameters for DBSCAN

[Tharindu Mathew]

Thanks Ryan. It seems maybe something like HAC or HDBScan maybe better for
my needs.

On Sun, Dec 30, 2018 at 11:51 PM Ryan Curtin <ryan at ratml.org> wrote:

> On Sun, Dec 30, 2018 at 11:42:54PM -0500, Tharindu Mathew wrote:
> > Hi,
> >
> > Would someone kindly point me to what range and point selection types are
> > available for dbscan? Going through header or API docs didn't help in
> this
> > case.
>
> Hey there Tharindu,
>
> I dug into it a little bit after seeing your IRC messages.  You can see
> my responses here:
>
> http://mlpack.org/irc/mlpack.20181230.html
>
> Actually I ended up noticing that PointSelectionPolicy isn't even used,
> so I opened an issue about it:
>
> https://github.com/mlpack/mlpack/issues/1625
>
> For the RangeSearchType, that is more there in case someone wants to use
> a different algorithm for the range search portion of the algorithm.
> Right now mlpack::range::RangeSearch is the only option implemented in
> the library.  The results it will give are exact, so the only thing that
> would make a difference is if you, e.g., wanted to use RangeSearch with
> a different metric (RangeSearch itself has some template parameters), or
> replace it with a different algorithm that might run faster in your case
> or something (but like I said you'd need to hand-implement it, and it
> would just need to have a Search() function matching the API of
> RangeSearch).
>
> The biggest parameters that will make a difference for the DBSCAN
> clustering are epsilon and minPoints.  You might also consider trying
> some of the other clustering algorithms in mlpack, like MeanShift and
> KMeans.
>
> Hope this helps!
>
> --
> Ryan Curtin    | "This room is green."
> ryan at ratml.org |   - Kazan
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-- 
Regards,
Tharindu Mathew
http://tharindumathew.com
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