ensemble {OTclust} | R Documentation |
Generate an ensemble of partitions.
Description
Generate multiple clustering results (that is, partitions) based on multiple versions of perturbed data using a specified baseline clustering method.
Usage
ensemble(data, nbs, clust_param, clustering = "kmeans", perturb_method = 1)
Arguments
data |
– data that will be perturbed. |
nbs |
– the number of clustering partitions to be generated. |
clust_param |
– parameters for pre-defined clustering methods. If clustering is "kmeans", "Mclust", "hclust", this is an integer indicating the number of clusters. For "dbscan", a numeric indicating epsilon. For "HMM-VB", a list of parameters. |
clustering |
– baseline clustering methods. User specified functions or example methods included in package ("kmeans", "Mclust", "hclust", "dbscan", "HMM-VB") can be used. Refer to the Detail. |
perturb_method |
– adding noise is |
Value
a matrix of cluster labels of the ensemble partitions. Each column is cluster labels of an individual clustering result.
Examples
data(sim1)
# the number of clusters.
C = 4
ens.data = ensemble(sim1$X[1:10,], nbs=10, clust_param=C, clustering="kmeans", perturb_method=1)