[R] How a clustering algorithm in R can end up with negative silhouette values?
Behnam.ABABAEI at limagrain.com
Fri Feb 19 20:55:18 CET 2016
Thank you for the response. But it is said in its description that after each run (sample), each observation in the whole dataset is assigned to the closest cluster. So how is it possible for one observation to be wrongly allocated, even with clara?
On Fri, Feb 19, 2016 at 11:48 AM -0800, "Sarah Goslee" <sarah.goslee at gmail.com<mailto:sarah.goslee at gmail.com>> wrote:
That means that points have been assigned to the wrong groups. This
may readily happen with a clustering method like cluster::clara() that
uses a subset of the data to cluster a dataset too large to analyze as
a unit. Negative silhouette numbers strongly suggest that your
clustering parameters should be changed.
On Fri, Feb 19, 2016 at 6:33 AM, ABABAEI, Behnam
<Behnam.ABABAEI at limagrain.com> wrote:
> We know that clustering methods in R assign observations to the closest medoids. Hence, it is supposed to be the closest cluster each observation can have. So, I wonder how it is possible to have negative values of silhouette , while we are supposedly assign each observation to the closest cluster and the formula in silhouette method cannot get negative?
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