cluster_cmeans: Fuzzy c-means

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Fuzzy c-means

Description

Fuzzy c-means clustering using e1071::cmeans.

Usage

cluster_cmeans(centers = 2, m = 2, iter = 100, dist = "euclidean")

Arguments

centers	number of clusters
m	fuzziness parameter (m > 1)
iter	maximum number of iterations
dist	distance method passed to e1071::cmeans

Details

Produces soft membership for each cluster. The hard assignment is returned by cluster(). Membership degrees are returned in the membership attribute.

Value

returns a fuzzy clustering object.

References

Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms.

Examples

data(iris)
model <- cluster_cmeans(centers = 3, m = 2)
model <- fit(model, iris[,1:4])
clu <- cluster(model, iris[,1:4])
table(clu)

daltoolbox documentation built on Feb. 10, 2026, 9:06 a.m.