Entering edit mode
Eisen's cluster software implements average linkage clustering by
replacing
nodes with an average of the leaf nodes represented by the node and by
then
computing distances from that average. hclust(), on the other hand,
uses an
average of the distances between all pairs of points in two nodes.
Does anyone have any information/opinion as to why one method might be
better
than the other?
Also, does anyone know of any code in R that implements Eisen's
algorithm?
Thanks.
-Ben