Description Usage Arguments Examples
find_clusters
uses breadth-first search to identify the connected components of the corresponding
adjacency graph of the centroid differences vectors.
1 |
A |
adjacency matrix |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Clusterpaths for Mammal Dentition
data(mammals)
X <- as.matrix(mammals[,-1])
X <- t(scale(X,center=TRUE,scale=FALSE))
n <- ncol(X)
## Pick some weights and a sequence of regularization parameters.
k <- 5
phi <- 0.5
w <- kernel_weights(X,phi)
w <- knn_weights(w,k,n)
gamma <- seq(0.0,43, length.out=100)
## Perform clustering
nu <- AMA_step_size(w,n)
sol <- cvxclust_path_ama(X,w,gamma,nu=nu)
## Construct adjacency matrix
A <- create_adjacency(sol$V[[10]],w,n)
find_clusters(A)
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