esmbl.stability {bootcluster} | R Documentation |
Estimate the stability of a clustering based on non-parametric bootstrap out-of-bag scheme, with option for subsampling scheme
Description
Estimate the stability of a clustering based on non-parametric bootstrap out-of-bag scheme, with option for subsampling scheme
Usage
esmbl.stability(
x,
k,
scheme = "kmeans",
B = 100,
hc.method = "ward.D",
cut_ratio = 0.5,
dist_method = "euclidean"
)
Arguments
x |
|
k |
number of clusters for which to estimate the stability |
scheme |
clustering method to use ("kmeans", "hc", or "spectral") |
B |
number of bootstrap re-samples |
hc.method |
hierarchical clustering method (default: "ward.D") |
cut_ratio |
ratio for subsampling (default: 0.5) |
dist_method |
distance method for spectral clustering (default: "euclidean") |
Details
This function estimates the stability through out-of-bag observations It estimate the stability at the (1) observation level, (2) cluster level, and (3) overall.
Value
- membership
vector of membership for each observation from the reference clustering
- obs_wise
vector of estimated observation-wise stability
- clust_wise
vector of estimated cluster-wise stability
- overall
numeric estimated overall stability
- Smin
numeric estimated Smin through out-of-bag scheme
Author(s)
Tianmou Liu
Examples
set.seed(123)
data(iris)
df <- iris[,1:4]
result <- esmbl.stability(df, k=3, scheme="kmeans")