Initialization of membership matrix using simple random sampling
Initializes the membership degrees matrix which is used to start a fuzzy and possibilistic partitioning clustering algorithm.
imembrand(n, k, mtype, numseed)
n |
an integer for the number of objects in the data set. |
k |
an integer for the number of clusters. |
mtype |
a string for any of three random initialization methods. The default method is f1 for fuzzy memberships. The options are f2 and f3 for fuzzy memberships and h for hard (crisp) memberships. |
numseed |
a number to be used for the seed of RNG. |
The function imembrand generates a numeric matrix containing the initial membership degrees by using simple random sampling technique.
an object of class ‘inaparc’, which is a list consists of the following items:
u |
a numeric matrix containing the crisp initial membership degrees of n objects to k clusters. |
call |
a string containing the matched function call that generates this ‘inaparc’ object. |
Zeynel Cebeci, Cagatay Cebeci
data(iris) n <- dim(iris)[1] # Generate a fuzzy membership degrees matrix using default values u <- imembrand(n=n, k=5)$u head(u) tail(u) # Generate a fuzzy membership degrees matrix using the method 3 u <- imembrand(n=n, k=5, mtype="f3", numseed=123)$u head(u) tail(u) # Generate a crisp membership degrees matrix u <- imembrand(n=n, k=5, mtype="h")$u head(u) tail(u)
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