K-means clustering uses the mean value for each cluster and minimizes the distance to individual observations.

Name: K-means clustering uses the mean value for each cluster and minimizes the distance to individual observations.
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K-means clustering algorithm partitions the data into K clusters, each represented by the mean (centroid) of its points, and minimizes the sum of squared distances between each point and its cluster centroid.

K-Means Clustering Uses the Mean Value for Each Cluster and Minimizes