betaCV
BetaCV
function to calculates the BetaCV.
- Keywords
- betaCV, cluster validation
Usage
betaCV(clust,dist)Arguments
- clust
Determine in which cluster a data is belonged. clust should be a numeric, 0 indicates a noise and cluster start at 1.
- dist
Distance matrix
Details
BetaCV measures how well the clusters based on compactness (intra-cluster distance) and separability (inter-cluster distance). BetaCV is the ratio between the average of intra-cluster distance to the average of inter-claster distance. The smaller BetaCV value indicates the better the clustering.
Value
This function returns the betaCV value.
References
University of Illinois. (2020, January 10). 6.1 Methods for Clustering Validation. Retrieved from Coursera: https://www.coursera.org/lecture/cluster-analysis/6-1-methods-for-clustering-validation-k59pn
See Also
https://www.coursera.org/lecture/cluster-analysis/6-1-methods-for-clustering-validation-k59pn
Examples
# NOT RUN {
x <- runif(20,-1,1)
y <- runif(20,-1,1)
dataset <- cbind(x,y)
l <- lsdbc(dataset, 7,3,"euclidean")
dmat <- as.matrix(dist(dataset,"euclidean"))
betaCV(l$cluster,dmat)
# }