Before revision:   We provide upper and lower bounds on this price as well as efficient algorithms to build explainable clustering for the k-means, k-medians, k-center and the maximum-spacing problems in a natural model in which explainability is achieved via decision trees  ]  .
After revision:  Here, we study this price for the following clustering problems: k-means, k-medians, k-centers and maximum-spacing. We provide upper and lower bounds on this price as well as efficient algorithms to build explainable clustering for the k-means, k-medians, k-center and the maximum-spacing problems in a natural model in which explainability is achieved via decision trees ] .