Kmeans creates clusters of spherical shape in which the radius is equal to the distance between the centroid and the farthest point. Therefore, it doesn’t work well when
- the data contains outliers.
- the density spread of the data points across the data space is different.
- the clusters are in different non-convex shapes such as elliptical clusters.