- # Perfect situation: all medoids "after stage 1" are good.
- medoids_K1 = bigmemory::as.big.matrix( sapply( 1:K1, function(i) s[[I(i,K1)]] ) )
- algoClust2 = function(dists,K) cluster::pam(dists,K,diss=TRUE)$id.med
- medoids_K2 = clusteringTask2(medoids_K1, K2, algoClust2, getRefSeries,
- n, 75, 4, 8, "little", verbose=TRUE, parll=FALSE)
+ # Perfect situation: all medoids "after stage 1" are ~good
+ algoClust2 <- function(dists,K) cluster::pam(dists,K,diss=TRUE)$id.med
+ indices2 <- clusteringTask2(1:K1, getSeries, K2, algoClust2, 210, 3, 4, 8, "little",
+ verbose=TRUE, parll=FALSE)
+ medoids_K2 <- getSeries(indices2)