Re:Introduction to K-Means Clustering
by isoprophlex on Monday March 14, 2022 @01:33PM
(#30675338)
That's a really pedantic take, nothing precludes you from using whatever distance function you want to get the distance to k centroids and act accordingly
Losing convergence guarantees is somewhat important!
Re:Introduction to K-Means Clustering
by isoprophlex on Monday March 14, 2022 @04:10PM
(#30677591)
I totally agree with your point, but sometimes you can get away by being handwavey about it and making sure the centroids aren't skipping all over the place... and that's good enough
K-means in its standard form does make a Euclidean hypothesis (it does not minimize a distance but the in-cluster variance).
It is not correct to use arbitrary distances because k-means may stop converging with other distance functions.
See this thread for more info: https://stats.stackexchange.com/questions/81481/why-does-k-m...