- clusters = hclust(dist(y)) #default distance : euclidean
- #cutree retourne les indices (? quel cluster indiv_i appartient) d'un clustering hierarchique
- clusterCut = cutree(clusters,k)
- Zinit1[,repet] = clusterCut
+ clusters = Mclust(matrix(c(X,Y),nrow=n),k) #default distance : euclidean
+ Zinit1[,repet] = clusters$classification