ClusterIndex: Cluster index for cluster evaluation
In jhmadsen/ClustTools: Clustering evaluation package

Description Usage Arguments Details Value Author(s) Examples

Function to evaluate clustering results by calculating the ratio between intra-cluster and inter-cluster distance

1	ClusterIndex(dist.obj, clusterVector)

`dist.obj`	An object of class 'dist' for dataset
`clusterVector`	A vector with integers indicating which cluster observations belong to

ClusterIndex computes the average distance for all observations, to observations in same cluster, and compare it with the average distance to observations in other clusters. The cluster index ranges from 0 to 1, where 0 indicates short distance to observations in same cluster, when compared to distance to observations on other clusters. 1 indicates equal distance to observations in same cluster as to observations in other clusters. The smaller the cluster index, the greater results are achieved with respect to intra- and inter-cluster distance. The theory is an extension of Tan, P.-N., Steinbach, M., Karpatne, A., & Kumar, V. (2005) idea of cohesion and separation

`avgDistCurrent`	Average distance for all observations to other observations in same cluster
`avgDistForeign`	Average distance for all observations to other observations in other clusters
`clusterindex`	The ratio between avgDistCurrent and avgDistForeign, i.e. avgDistCurrent/avgDistForeign

Jacob H. Madsen

## Select a dataset to standardize and cluster
X <- scale(iris[,1:4])

## Cluster the dataset with a given number of clusters
cluster.obj <- kmeans(X, 3)

## Evaluate the clustering results with 'ClusterIndex'
ClusterIndex(dist(X), cluster.obj$cluster)