CFuzzyMeans: calssical c-mean algorithm

In jejeplusfaim/geoCmeans:

Description

calssical c-mean algorithm

Usage

CFuzzyMeans(data, k, m, maxiter = 500, tol = 0.01, standardize = TRUE)

Arguments

data	A dataframe with only numerical variable
k	An integer describing the number of cluster to find
m	An integer for the fuzzyness degree
maxiter	An integer for the maximum number of iteration
tol	The tolerance criterion used in the evaluateMatrices function for convergence assessment
standardize	A boolean to specify if the variable must be centered and reduce (default = True)

Examples

mat1 <- rbind(c(0.45,0.55),c(0.35,0.65),c(0.8,0.2),c(0.5,0.5),c(0.9,0.1),c(0.7,0.3))
mat2 <- rbind(c(0.45,0.55),c(0.4,0.60),c(0.8,0.2),c(0.45,0.55),c(0.95,0.05),c(0.7,0.3))
evaluateMatrices(mat1,mat2,0.01)

jejeplusfaim/geoCmeans documentation built on Dec. 23, 2019, 7:31 p.m.