multiview_pam_gen {ConsensusClustering} | R Documentation |
Multiview PAM (K-medoids) generation
Description
Multiview PAM (K-medoids) generation
Usage
multiview_pam_gen(
X,
rep = 10,
range.k = c(2, 5),
is.distance = FALSE,
method = "random",
sample.set = NA
)
Arguments
X |
List of input data matrices of Sample x feature or distance matrices.
The length of |
rep |
number of repeats |
range.k |
vector of minimum and maximum values for k |
is.distance |
binary balue indicating if the input |
method |
method for the choice of k at each repeat |
sample.set |
vector of samples the clustering is being applied on. can be names or indices.
if |
Details
At each repeat, k is selected randomly or based on the best silhouette width from a discrete uniform distribution between range.k[1] and range.k[2]. Then PAM clustering is applied and result is returned.
Value
matrix of clusterings Nsample x (Nrepeat x Nviews)
Examples
data = multiview_clusters (n = c(40,40,40), hidden.dim = 2, observed.dim = c(2,2,2),
sd.max = .1, sd.noise = 0, hidden.r.range = c(.5,1))
X_observation = data[["observation"]]
Clusters = multiview_pam_gen(X_observation)