Description Usage Arguments Value References Examples
Compute Silhouette index for a given partition of a data set.
1 | get_Silhouette(y, mem, disMethod = "Euclidean")
|
y |
data matrix which is an R matrix object (for dimension > 1) or vector object (for dimension = 1) with rows be observations and columns be variables. |
mem |
vector of the cluster membership of data points. The cluster membership takes values: 1, 2, …, g, where g is the estimated number of clusters. |
disMethod |
specification of the dissimilarity measure. The available measures are “Euclidean” and “1-corr”. |
A list of 3 elements:
avg.s |
average Sihouette index. |
s |
vector of Sihouette indices for data points. |
neighbor |
a vector, the $i$-th element of which indicates which cluster is the nearest neighbor cluster of the $i$-th data point. |
Kaufman, L., Rousseeuw, P.J., (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York.
Wang, S., Qiu, W., and Zamar, R. H. (2007). CLUES: A non-parametric clustering method based on local shrinking. Computational Statistics & Data Analysis, Vol. 52, issue 1, pages 286-298.
1 2 3 4 5 6 7 8 9 | data(Maronna)
# data matrix
maronna <- Maronna$maronna
# cluster membership
maronna.mem <- Maronna$maronna.mem
tt <- get_Silhouette(maronna, maronna.mem)
tt$avg.s
|
[1] 0.5498086
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