[Qgis-user] Draw Ellipse/Polygons for areas of maximum concentration

[Nyall Dawson]

On Fri, 30 Apr 2021 at 08:25, krishna Ayyala <ayyalakrishna at gmail.com>
wrote:

> Chris,
> Thanks for the reply. Yes, I did run k-means clustering for 4 clusters. It
> is creating a new layer called "clusters". This layer has a field called
> Cluster_id, ranging from 1 to 4. But, this method is considering all the
> points within the circle. I am looking for the points outside the ellipses
> to be omitted (should not be considered)
>

In this case "dbscan clustering" is more appropriate.


> . Also K-means clustering is not generating any polygons/ellipses. We have
> to identify a cluster based on the Cluster_ID. I am curious if there is any
> tool within Qgis that can produce results similar to the circle with
> ellipses?
>

What you could do is dissolve the points based on the cluster_id field, and
then generate convex (or concave) hulls enclosing each set of points. You
won't get ellipses, but you'll get polygons describing the boundaries. (And
it would be relatively straightforward to wrap up these steps into a single
graphical model so that you have one tool which gives the desired output!).

Nyall




>
> Regards.
>
> On Thu, Apr 29, 2021 at 3:56 PM chris hermansen <clhermansen at gmail.com>
> wrote:
>
>> Krishna and list,
>>
>> On Thu, Apr 29, 2021 at 2:51 PM krishna Ayyala <ayyalakrishna at gmail.com>
>> wrote:
>>
>>> Hello,
>>> I have a circle in which there are randomly distributed points as below.
>>> Each point is a customer.
>>>
>>> [image: image.png]
>>>
>>>
>>> Is there a tool within QGIS that can automatically generate four
>>> polygons or four ellipses such as below. These polygons are the areas of
>>> maximum concentration of the customers?
>>>
>>> [image: image.png]
>>>
>>> You could try k-means clustering
>>
>>
>> https://docs.qgis.org/3.4/en/docs/user_manual/processing_algs/qgis/vectoranalysis.html#k-means-clustering
>>
>> --
>> Chris Hermansen · clhermansen "at" gmail "dot" com
>>
>> C'est ma façon de parler.
>>
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