Fuzzy Analysis (FANNY) Object
fanny.object.RdThe objects of class "fanny" represent a fuzzy clustering of a
dataset.
GENERATION
These objects are returned from fanny.
INHERITANCE
The class "fanny" inherits from "partition".
Therefore, the generic functions plot and clusplot can
be used on a fanny object.
Value
A legitimate fanny object is a list with the following components:
- membership
matrix containing the memberships for each pair consisting of an observation and a cluster.
- memb.exp
the membership exponent used in the fitting criterion.
- coeff
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.
- clustering
the clustering vector of the nearest crisp clustering, see
partition.object.- k.crisp
integer (\(\le k\)) giving the number of crisp clusters; can be less than \(k\), where it's recommended to decrease
memb.exp.- objective
named vector containing the minimal value of the objective function reached by the FANNY algorithm and the relative convergence tolerance
tolused.- convergence
named vector with
iterations, the number of iterations needed andconvergedindicating if the algorithm converged (inmaxititerations within convergence tolerancetol).- diss
an object of class
"dissimilarity", seepartition.object.- call
generating call, see
partition.object.- silinfo
list with silhouette information of the nearest crisp clustering, see
partition.object.- data
matrix, possibibly standardized, or NULL, see
partition.object.