fanny.object: Fuzzy Analysis (FANNY) Object
Description
The objects of class "fanny"
represent a fuzzy clustering of a
dataset.
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 ($<= k$)="" 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
.
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.