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fussclust

The goal of fussclust is to provide methods for fuzzy unsupervised and semi-supervised clustering, including fuzzy, possibilistic, and hybrid models.

Installation

You can install the development version of fussclust from GitHub with:

# install.packages("devtools")
devtools::install_github("kkmita/fussclust")

Example

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)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.