Description Usage Arguments Value Examples
Perform kmeans clustering and then calculates several external and internal clustering indecies. Parameters of kmeans clustering: iter.max = 1e+09; nstart = 1000.
1 | check_kmeans_clustering(w, n.dim, n.clusters, labs.known)
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w |
Transformed distance matrix (transformed before by transformation() function) |
n.dim |
Number of dimensions of |
n.clusters |
Expected number of clusters required by kmeans |
labs.known |
Ground truth clustering labels (known from the experiment) |
List of clustering indecies and clutering labels:
Adjusted Rand Index
Rand Index
Jaccard Index
Dunn Index
Davies Bouldin Index
Silhouette Index
Clustering labels of the cells
Known (from experiment) clustering labels of the cells
1 2 3 | labs.known <- as.numeric(colnames(quake))
w <- transformation(as.matrix(1 - cor(quake, method = "spearman")), "spectral")
check_kmeans_clustering(w, 4, 5, labs.known)
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