fanny.object: Fuzzy Analysis (FANNY) Object

Description

The objects of class "fanny" represent a fuzzy clustering of a dataset.

Arguments

Value

A legitimate fanny object is a list with the following components:
membershipmatrix containing the memberships for each pair consisting of an observation and a cluster.
memb.expthe membership exponent used in the fitting criterion.
coeffDunn'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.
clusteringthe clustering vector of the nearest crisp clustering, see partition.object.
k.crispinteger ($\le k$) giving the number of crisp clusters; can be less than $k$, where it's recommended to decrease memb.exp.
objectivenamed vector containing the minimal value of the objective function reached by the FANNY algorithm and the relative convergence tolerance tol used.
convergencenamed vector with iterations, the number of iterations needed and converged indicating if the algorithm converged (in maxit iterations within convergence tolerance tol).
dissan object of class "dissimilarity", see partition.object.
callgenerating call, see partition.object.
silinfolist with silhouette information of the nearest crisp clustering, see partition.object.
datamatrix, possibibly standardized, or NULL, see partition.object.

GENERATION

These objects are returned from fanny.

METHODS

The "fanny" class has methods for the following generic functions: print, summary.

INHERITANCE

The class "fanny" inherits from "partition". Therefore, the generic functions plot and clusplot can be used on a fanny object.