The VisuClust package provides functions to display the result of clusterings, if they are either disjoint  (every observation belongs to one cluster) or fuzzy (for each observation i and cluster k there is a value  u[i,k](i=1,...,nPoints; k=1,...,nClusters)), which states the membership of the i.th observation for the cluster k,  where sum(u[i,k],k=1,...,nClusters) = 1). A disjoint clustering can be created with known hierarchical methods,  if the desired number of clusters is provided, or by using k-means-clustering (for example \link{hclust}, \link{kmeans}  from the package cluster). A fuzzy clustering can be created for example with fanny from the package \link{cluster}.   The basis of the visualization is Sammon's method Nonlinear Mapping (NLM), which displays all observations in a plane so  that the distances in the multivariate space are approximated best (see \link{sammon} from the package MASS).  The clusters in the NLM diagram can be indicated by coloring, drawing lines between similar point pairs, and other features.