affiche_graphe: affiche_graphe du clustering results

In FaridaBenchalal/MIXCLUSTERING: MIXCLUSTERING

Description

the function outputs the loglikelihood and the clusters in 2D plot.

Usage

affiche_graphe(resultat_mixclust)

Arguments

resultat_mixclust

the output of MIXCLUSTERING.

Author(s)

Nour-Dass HAMMADI & Farida BENCHENLAL Student M2 Lyon 2 Lumiere University

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

library(bayess)
library(MASS)
library(mvtnorm)
library(dplyr)
library(FactoMineR)
library(factoextra)

x <- mtcars
x$vs = as.factor(x$vs)
x$am = as.factor(x$am)
x$gear = as.factor(x$gear)

## The function is currently defined as


function(resultat_mixclust){
  res.famd <- FAMD (x, ncp = 5, graph = FALSE)
  plot(res.famd$ind$coord[,1], res.famd$ind$coord[,2],
       # col = res$z, pch=19, xlab = "Composante 1", ylab = "Composante 2")
       col =  resultat_mixclust$z, pch=19, xlab = "Composante 1", ylab = "Composante 2")
}





set.seed(123)

mix_clust_kmeans <- My_Mix_clustering(x, 3, 20, 'kmeans')
mix_clust_random <- My_Mix_clustering(x, 3, 20, 'random')

par(mfrow = c(1,2))
affiche_graphe(mix_clust_kmeans)
affiche_graphe(mix_clust_random)

par(mfrow = c(1,2))
plot(mix_clust_kmeans$log_vrai, main = "Log_vraissemblance par Kmeans")
plot(mix_clust_random$log_vrai, main = "Log_vraissemblance par Random")
res.famd <- FAMD (x, ncp = 5, graph = FALSE)


par(mfrow = c(1,2))
plot(res.famd$ind$coord[,1], res.famd$ind$coord[,2],
     col = mix_clust_kmeans$z, pch=19, xlab = "Composante 1", ylab = "Composante 2", main = "Mix Clustering par Kmeans")
plot(res.famd$ind$coord[,1], res.famd$ind$coord[,2],
     col = mix_clust_random$z, pch=19, xlab = "Composante 1", ylab = "Composante 2", main = "Mix Clustering par Random")

FaridaBenchalal/MIXCLUSTERING documentation built on Dec. 17, 2021, 8:23 p.m.