clues (version 0.3.2)

Get.Silhouette: Compute Silhouette Index

Description

Compute Silhouette index for a given partition of a data set.

Usage

Get.Silhouette(y, mem, disMethod = "Euclidean")

Arguments

y

data matrix which is a 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 member ship takes values: $1$, $2$, $\ldots$, $g$, where $g$ is the estimated number of clusters.

disMethod

specification of the dissimilarity measure. The available measures are Euclidean and 1-corr.

Value

• 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.

References

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.

Examples

# ruspini data
data(Ruspini)
# data matrix
ruspini <- Ruspini$ruspini
mem <- Ruspini$ruspini.mem
 
tt <- Get.Silhouette(ruspini, mem)
tt$avg.s