| fanny.object {cluster} | R Documentation |
The objects of class "fanny" represent a fuzzy clustering of a
dataset.
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 (<= 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 tol used.
|
convergence |
named vector with iterations, the number of iterations needed
and converged indicating if the algorithm converged (in
maxit iterations within convergence tolerance tol).
|
diss |
an object of class "dissimilarity", see
partition.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. |
These objects are returned from fanny.
The "fanny" class has methods for the following generic functions:
print, summary.
The class "fanny" inherits from "partition".
Therefore, the generic functions plot and clusplot can
be used on a fanny object.
fanny, print.fanny,
dissimilarity.object,
partition.object, plot.partition.