Question: what is the difference between k means and k medoids?
Answer: Both the k -means and k -medoids algorithms are partitional (breaking the dataset up into groups). ... K-means attempts to minimize the total squared error, while k-medoids minimizes the sum of dissimilarities between points labeled to be in a cluster and a point designated as the center of that cluster.