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 <ahow...@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...@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 >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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