Content deleted Content added
Assessment: Computer science: class=C; Databases: class=C (assisted) |
No edit summary |
||
Line 43:
There is a 1967 paper, published in Psychometrika, titled "Hierarchical Clustering Schemes", by S. C. Johnson (yes, that's me...). It was extensively cited in the 70's and 80's, in part because Bell Labs gave away a FORTRAN program for free that did a couple of the methods described in the paper. The paper pointed out that there is a correspondence between hierarical clusterings and a kind of data metric called an ultrametric -- whenever you have a hierarchical clustering, it implies an ultrametic, and conversely. [[Special:Contributions/76.244.36.165|76.244.36.165]] ([[User talk:76.244.36.165|talk]]) 19:14, 18 October 2012 (UTC) Stephen C Johnson
Example for Agglomerative Clustering edit
I changed The "increase" in variance for the cluster being merged (Ward's method[7]) to The "decrease" in variance for the cluster being merged (Ward's method[7]).
So it is also above, to Cluster dissimilarity and so appears from Ward's method, https://en.wikipedia.org/wiki/Ward%27s_method
Still this doesn't appears yet in text.
| |||