The goal of fussclust is to provide methods for fuzzy
unsupervised and semi-supervised clustering, including fuzzy,
possibilistic, and hybrid models.
You can install the development version of fussclust
from GitHub with:
# install.packages("devtools")
devtools::install_github("kkmita/fussclust")This is a basic example which shows how to fit unsupervised and semi-supervised models.
library(fussclust)
X <- matrix(rnorm(100), ncol = 2)
model_fcm <- fussclust::FCM(X = X, C = 2)
model_pcm <- fussclust::PCM(X = X, C = 2)
superF <- matrix(0, nrow = nrow(X), ncol = ncol(X))
superF[1:10, 1] <- 1
superF[20:30, 2] <- 1
model_ssfcm <- fussclust::SSFCM(X = X, C = 2, superF = superF, alpha = 1)
model_sspcm <- fussclust::SSPCM(X = X, C = 2, superF = superF, alpha = 1)