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FAKMCT

Fuzzy Adaptive Resonance Theory K-Means Clustering Technique (FAKMCT)

Authors

Alfi Nurrahmah

Maintainer

Alfi Nurrahmah 221810140@stis.ac.id

Functions

fakmct : A set of function for clustering data observation with hybrid method Fuzzy ART and K-Means

Examples

library(fakmct)
# Using dataset iris
## load data
data.inputs = iris[,-5]
true.labels = as.numeric(unlist(iris$Species))

## run model data
ex.iris<-fakmct(data.inputs, alpha = 0.3, rho = 0.5, beta = 1, max_epochs = 50, max_clusters = 5)
ex.iris$labels
ex.iris$size
ex.iris$centroids
ex.iris$params

## plot data
plot(data.inputs, col = ex.iris$labels, pch = true.labels,
     main = paste0("Dataset: Iris"))

# Using data IPM 2019

## load simulate data IPM
data("simulatedataIPM")
dt <- simulatedataIPM

## run model data IPM
mod.fakm<-fakmct(dt, alpha = 0.3, rho = 0.5, beta = 0.1, max_epochs = 50, max_clusters = 5)
mod.fakm$labels
mod.fakm$size
mod.fakm$centroids
mod.fakm$params

## plot data IPM
plot(dt, col = mod.fakm$labels, pch=mod.fakm$labels, main = paste0("Dataset Human Development Index (IPM)"))

References

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