K-means is a popular clustering algorithm used to partition data into distinct, non-overlapping groups. It helps uncover hidden patterns or rethink existing categories.
Conditions: Data must be partitionable into distinct groups.; Groups are non-overlapping.
K-means is a popular clustering algorithm used to partition data into distinct, non-overlapping groups. It helps uncover hidden patterns or rethink existing categories.
Conditions: Data must be partitionable into distinct groups.; Groups are non-overlapping.
The object returned by the kmeans function contains a cluster assignment for each data point and the coordinate location of the center of each cluster.
The object returned by the kmeans function contains a cluster assignment for each data point and the coordinate location of the center of each cluster.