cmeans {clustering} R Documentation

the cmeans algorithm module

Description


Fuzzy clustering (also referred to as soft clustering) is a form of clustering in which
each data point can belong to more than one cluster.

Clustering Or cluster analysis involves assigning data points to clusters (also called buckets,
bins, Or classes), Or homogeneous classes, such that items in the same class Or cluster are as
similar as possible, while items belonging to different classes are as dissimilar as possible.
Clusters are identified via similarity measures. These similarity measures include distance,
connectivity, And intensity. Different similarity measures may be chosen based on the data Or
the application.

>https://en.wikipedia.org/wiki/Fuzzy_clustering

Usage

cmeans(dataset,
    centers = 3,
    fuzzification = 2,
    threshold = 0.001);

Arguments

dataset

-

centers

[as integer]

fuzzification

[as double]

threshold

[as double]

env

[as Environment]

Details

Authors

MLkit

Value

this function returns data object of type Classify.

clr value class

Examples


[Package clustering version 1.0.0.0 Index]