Storage class for the results of a clustering algorithm applied on an
Dissimilarity metric used in the form of a one-element
Dimensionality of the clustered points in the form of a one-element
Clustering algorithm (and optionally, type) as a
character vector of length 1 or 2.
Resulting object after applying the clustering algorithm on a dataset.
Cluster assignments for the samples in the dataset as a matrix. Row names in this matrix are sample identifiers, and each column is dedicated to partitioning into k clusters for a fixed k.
numeric vector of mean silhouette values for each tested value of k.
Gets the identifiers of all samples used in the clustering.
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