Fuzzy Analysis (FANNY) Object
The objects of class
"fanny" represent a fuzzy clustering of a
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 (\(\le k\)) giving the number of crisp
clusters; can be less than \(k\), where it's recommended to
named vector containing the minimal value of the objective function
reached by the FANNY algorithm and the relative convergence
named vector with
iterations, the number of iterations needed
converged indicating if the algorithm converged (in
maxit iterations 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
"fanny" class has methods for the following generic functions:
"fanny" inherits from
Therefore, the generic functions
be used on a