K-medoids
id:
k-medoids-272-12930280
title:
K-medoids
text:
The k-medoids problem is a clustering problem similar to k-means. The name was coined by Leonard Kaufman and Peter J. Rousseeuw with their PAM algorithm. Both the k-means and k-medoids algorithms are partitional and attempt to minimize the distance between points labeled to be in a cluster and a point designated as the center of that cluster. In contrast to the k-means algorithm, k-medoids chooses actual data points as centers, and thereby allows for greater interpretability of the cluster cente
brand slug:
wiki
category slug:
encyclopedia
description:
Clustering algorithm minimizing the sum of distances to k representatives
original url:
https://en.wikipedia.org/wiki/K-medoids
date created:
date modified:
2023-12-02T08:13:53Z
main entity:
{"identifier":"Q3191282","url":"https://www.wikidata.org/entity/Q3191282"}
image:
fields total:
13
integrity:
14