View source: R/ClusterStability.R
ClusterStability | R Documentation |
This function will return the individual stability score ST and the global score STglobal using either the K-means or K-medoids algorithm and four different clustering indices: Calinski-Harabasz, Silhouette, Dunn or Davies-Bouldin.
ClusterStability(dat, k, replicate, type)
dat |
the input dataset: either a matrix or a dataframe. |
k |
the number of classes for the K-means or K-medoids algorithm (default=3). |
replicate |
the number of replicates to perform (default=1000). |
type |
the algorithm used in the partitioning: either 'kmeans' or 'kmedoids' algorithm (default=kmeans). |
Returns the individual (ST) and global (ST_global) stability scores for the four clustering indices: Calinski-Harabasz (ch), Silhouette (sil), Dunn (dunn) or Davies-Bouldin (db).
## Calculates the stability scores of individual objects of the Iris dataset
## using K-means, 100 replicates (random starts) and k=3
ClusterStability(dat=iris[1:4],k=3,replicate=100,type='kmeans');
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