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Ajout scripts CAH

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This commit is contained in:
Louis Lacoste 2024-05-07 16:07:54 +02:00
parent be61e5f6f8
commit 58a4599213
2 changed files with 96 additions and 5 deletions
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12
03_CAH_clust.R → 03_CAH_clust_toutes_dominantes.R
View file

@ -6,7 +6,7 @@ library(here)
library(ggplot2)
library(ggdendro)
library(factoextra)
set.seed(1234)
data <- data.frame(read.csv(file.path(here(), "data", "02_preprocessed_data.csv"),
header = TRUE
), stringsAsFactors = TRUE)
@ -23,7 +23,7 @@ data <- data %>%
mutate_if(sapply(data, is.character), as.factor)
selected_cols <- c(
"parcours", "domaine2A", "1AC-MI",
"dominante3A", "parcours", "domaine2A", "1AC-MI",
"2A-UEchoix-S1-UC1", "2A-UEchoix-S1-UC2", "2A-UEchoix-S2-UC4",
"2A-UEchoix-S2-UC3", "2A-UEchoix-S2-UC5", "2A-UEchoix-S2-UC6",
"2A-Projet-S2", "1AC-OUVERTURE"
@ -32,7 +32,7 @@ selected_cols <- c(
onehot_data <- one_hot(as.data.table(data), cols = selected_cols, sparsifyNAs = TRUE)
#  Fonctionne bien avec binary
dist_eucl <- dist(x = onehot_data[, -c(1, 2, 3)], method = "binary")
dist_eucl <- dist(x = onehot_data[, - 1], method = "binary")
hclust_avg <- hclust(dist_eucl, method = "average")
@ -45,10 +45,12 @@ p <- ggplot(segment(plotdata)) +
scale_y_reverse(expand = c(0.2, 0))
p + theme_dendro()
fviz_nbclust(onehot_data[, -c(1,2,3)], FUNcluster = hcut, k.max = 30)
fviz_nbclust(onehot_data[, -c(1, 2, 3)], FUNcluster = hcut, k.max = 30, method = "wss")
cut_avg <- cutree(hclust_avg, k = 6)
names(cut_avg) <- data[["ine"]]
table(cut_avg)
onehot_data[["cluster"]] <- cut_avg
data[["cluster"]] <- cut_avg
write.csv(data, file.path(here(), "data", "03_cah_results.csv"), row.names = FALSE)

89
04_CAH_clust_par_dominantes.R Normal file
View file

@ -0,0 +1,89 @@
library(data.table)
library(mltools)
library(dplyr)
library(tidyr)
library(here)
library(ggplot2)
library(ggdendro)
library(factoextra)
set.seed(1234)
data <- data.frame(read.csv(file.path(here(), "data", "02_preprocessed_data.csv"),
header = TRUE
), stringsAsFactors = TRUE)
data_folder_path <- file.path(here(), "data", "04_CAH_par_dominante")
if (!dir.exists(data_folder_path)) {
dir.create(data_folder_path)
}
colnames(data)[5:ncol(data)] <- c(
"1AC-OUVERTURE", "1AC-MI",
"2A-UEchoix-S1-UC1", "2A-UEchoix-S1-UC2", "2A-UEchoix-S2-UC3",
"2A-UEchoix-S2-UC4",
"2A-UEchoix-S2-UC5", "2A-UEchoix-S2-UC6",
"2A-Projet-S2"
)
data <- data %>%
mutate_if(sapply(data, is.character), as.factor)
selected_cols <- c(
"dominante3A", "parcours", "domaine2A", "1AC-MI",
"2A-UEchoix-S1-UC1", "2A-UEchoix-S1-UC2", "2A-UEchoix-S2-UC4",
"2A-UEchoix-S2-UC3", "2A-UEchoix-S2-UC5", "2A-UEchoix-S2-UC6",
"2A-Projet-S2", "1AC-OUVERTURE"
)
seuil_effectif <- 20L
#  On récupère les dominantes supérieures au seuil
vec_dominantes <- na.omit(sapply(unique(data[["dominante3A"]]), function(dominante) {
ifelse(sum(data[["dominante3A"]] == dominante) > seuil_effectif,
as.character(dominante), NA
)
}))
for (dominante in vec_dominantes) {
message("Dominante ", dominante)
data_dominante <- data %>% filter(dominante3A == dominante)
onehot_data <- one_hot(as.data.table(data_dominante), cols = selected_cols, sparsifyNAs = TRUE)
#  Fonctionne bien avec binary
dist <- dist(x = onehot_data[, -1], method = "binary")
hclust_avg <- hclust(dist, method = "average")
dhc <- as.dendrogram(hclust_avg)
plotdata <- dendro_data(dhc, type = "rectangle")
p <- ggplot(segment(plotdata)) +
geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
coord_flip() +
scale_y_reverse(expand = c(0.2, 0)) +
ggtitle(paste0("Dominante : ", dominante))
p + theme_dendro()
print(fviz_nbclust(onehot_data,
FUNcluster = hcut
)+
ggtitle(paste0("Dominante : ", dominante)))
nb_clust_dominante <- as.integer(readline(prompt = paste0(
"Nb clusters ",
dominante,
" : "
)))
cut_avg <- cutree(hclust_avg, k = nb_clust_dominante)
names(cut_avg) <- data_dominante[["ine"]]
table(cut_avg)
data_dominante[["cluster"]] <- cut_avg
write.csv(data_dominante, file.path(
data_folder_path,
paste0("04_", dominante, "_cah_results.csv")
), row.names = FALSE)
}