The objects of class
"fanny" represent a fuzzy clustering of a dataset.
fanny object is a list with the following components:
- matrix containing the memberships for each pair consisting of an observation and a cluster.
- the membership exponent used in the fitting criterion.
- Dunn's partition coefficient F(k) of the clustering, where k is the number of clusters. F(k) is the sum of all squared membership coefficients, divided by the number of observations. Its value is between 1/k and 1.
The normalized form of the coefficient is also given. It is defined as (F(k) - 1/k) / (1 - 1/k), and ranges between 0 and 1. A low value of Dunn's coefficient indicates a very fuzzy clustering, whereas a value close to 1 indicates a near-crisp clustering.
- the clustering vector of the nearest crisp clustering, see
- integer (<= k) giving the number of crisp clusters; can be less than k, where it's recommended to decrease
- named vector containing the minimal value of the objective function reached by the FANNY algorithm and the relative convergence tolerance
- named vector with
iterations, the number of iterations needed and
convergedindicating if the algorithm converged (in
maxititerations within convergence tolerance
- an object of class
- generating call, see
- list with silhouette information of the nearest crisp clustering, see
- matrix, possibibly standardized, or NULL, see
These objects are returned from
Documentation reproduced from package cluster, version 2.0.4. License: GPL (>= 2)