cluster_by_kmeans | R Documentation |
Cluster similarity matrix by k-means clustering
cluster_by_kmeans(mat, max_k = max(2, min(round(nrow(mat)/5), 100)), ...)
mat |
The similarity matrix. |
max_k |
maximal k for k-means clustering. |
... |
Other arguments passed to |
The best number of k for k-means clustering is identified according to the "elbow" or "knee" method on the distribution of within-cluster sum of squares (WSS) at each k.
A vector of cluster labels (in numeric).
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