[scikit-learn] Drawing contours in KMeans

[Mahmood Naderan]

 >Mebbe principal components analysis would suggest an
>ellipsoid containing "most" of the points in a "cloud".

Sorry I didn't understand. Can you explain more?
Regards,
Mahmood




On Wed, Dec 9, 2020 at 8:55 PM The Helmbolds via scikit-learn <
scikit-learn at python.org> wrote:

> [scikit-learn] Drawing contours in KMeans4
>
>
> Mebbe principal components analysis would suggest an ellipsoid containing
> "most" of the points in a "cloud".
>
>
>
>
> "You won't find the right answers if you don't ask the right questions!"
> (Robert Helmbold, 2013)
>
>
> On Wednesday, December 9, 2020, 12:22:49 PM MST, Andrew Howe <
> ahowe42 at gmail.com> wrote:
>
>
> Ok, I see. Well the attached notebook demonstrates doing this by simply
> finding the maximum distance from each centroid to it's datapoints and
> drawing a circle using that radius. It's simple, but will hopefully at
> least point you in a useful direction.
> [image: image.png]
> Andrew
>
> <~~~~~~~~~~~~~~~~~~~~~~~~~~~>
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>
>
> On Wed, Dec 9, 2020 at 12:59 PM Mahmood Naderan <mahmood.nt at gmail.com>
> wrote:
>
> I mean a circle/contour to group the points in a cluster for better
> representation.
> For example, if there are 6 six clusters, it will be more meaningful to
> group large data points in a circle or contour.
>
> Regards,
> Mahmood
>
>
>
>
> On Wed, Dec 9, 2020 at 11:49 AM Andrew Howe <ahowe42 at gmail.com> wrote:
>
> Contours generally indicate a third variable - often a probability
> density. Kmeans doesn't provide density estimates, so what precisely would
> you want the contours to represent?
>
> Andrew
>
> <~~~~~~~~~~~~~~~~~~~~~~~~~~~>
> J. Andrew Howe, PhD
> LinkedIn Profile <http://www.linkedin.com/in/ahowe42>
> ResearchGate Profile <http://www.researchgate.net/profile/John_Howe12/>
> Open Researcher and Contributor ID (ORCID)
> <http://orcid.org/0000-0002-3553-1990>
> Github Profile <http://github.com/ahowe42>
> Personal Website <http://www.andrewhowe.com>
> I live to learn, so I can learn to live. - me
> <~~~~~~~~~~~~~~~~~~~~~~~~~~~>
>
>
> On Wed, Dec 9, 2020 at 9:41 AM Mahmood Naderan <mahmood.nt at gmail.com>
> wrote:
>
> Hi
> I use the following code to highlight the cluster centers with some red
> dots.
>
> kmeans = KMeans(n_clusters=6, init='k-means++', max_iter=100, n_init=10,
> random_state=0)
> pred_y = kmeans.fit_predict(a)
> plt.scatter(a[:,0], a[:,1])
> plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1],
> s=100, c='red')
> plt.show()
>
> I would like to know if it is possible to draw contours over the clusters.
> Is there any way for that?
> Please let me know if there is a function or option in KMeans.
>
> Regards,
> Mahmood
>
>
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