Frequently Asked Questions

Explain Some Cases Where K-Means Clustering Fails to Give Good Results?

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.

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