Timeline for What clustering algorithm can be used with a distance matrix and without feaures?
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| May 2, 2014 at 19:27 | comment | added | Has QUIT--Anony-Mousse | @whuber The reason for the -1 is mostly that computing distances to centroids is exactly what is not possible here. He is clustering executable files (see his previous question), which he compares by compression distance. What is the centroid of a bunch of executables? | |
| May 2, 2014 at 15:13 | comment | added | whuber♦ | @Anony You might be a little too harsh here. If we read this answer just a little more generously and understand "based on ... distance" to include squared distances, then it is a mathematical fact that one-half the sum of pairwise squared distances within a cluster equals the sum of squared distances to the centroids. | |
| May 2, 2014 at 14:07 | comment | added | Has QUIT--Anony-Mousse | -1: k-means is not based on pairwise distances. On the contrary. It is based on sum of squared 1d deviations from centroids only. | |
| May 2, 2014 at 9:36 | history | answered | doug | CC BY-SA 3.0 |