theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_20_50_3_4.png",plot=plot_test_accuracy_20_50_3_4)
stats_table_test_accuracy_20_50_3_4 <- results_20_50_3_4 %>%
select(all_of(selected_20_50_3_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_20_50_3_4, "test_accuracy/stats_table_test_accuracy_20_50_3_4.csv")
results_20_50_2_4<- read_csv("results_with_D=20,p=50,q=2,K=4.csv")
selected_20_50_2_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_20_50_2_4_test_accuracy <- results_20_50_2_4 %>%
select(selected_20_50_2_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_20_50_2_4_test_accuracy$Variable <- factor(
df_long_20_50_2_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_20_50_2_4<-ggplot(df_long_20_50_2_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=20,p=50,q=2,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_20_50_2_4.png",plot=plot_test_accuracy_20_50_2_4)
stats_table_test_accuracy_20_50_2_4 <- results_20_50_2_4 %>%
select(all_of(selected_20_50_2_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_20_50_2_4, "test_accuracy/stats_table_test_accuracy_20_50_2_4.csv")
results_20_35_3_4<- read_csv("results_with_D=20,p=35,q=3,K=4.csv")
selected_20_35_3_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_20_35_3_4_test_accuracy <- results_20_35_3_4 %>%
select(selected_20_35_3_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_20_35_3_4_test_accuracy$Variable <- factor(
df_long_20_35_3_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_20_35_3_4<-ggplot(df_long_20_35_3_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=20,p=35,q=3,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_20_35_3_4.png",plot=plot_test_accuracy_20_35_3_4)
stats_table_test_accuracy_20_35_3_4 <- results_20_35_3_4 %>%
select(all_of(selected_20_35_3_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_20_35_3_4, "test_accuracy/stats_table_test_accuracy_20_35_3_4.csv")
results_20_35_2_4<- read_csv("results_with_D=20,p=35,q=2,K=4.csv")
selected_20_35_2_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_20_35_2_4_test_accuracy <- results_20_35_2_4 %>%
select(selected_20_35_2_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_20_35_2_4_test_accuracy$Variable <- factor(
df_long_20_35_2_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_20_35_2_4<-ggplot(df_long_20_35_2_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=20,p=35,q=2,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_20_35_2_4.png",plot=plot_test_accuracy_20_35_2_4)
stats_table_test_accuracy_20_35_2_4 <- results_20_35_2_4 %>%
select(all_of(selected_20_35_2_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_20_35_2_4, "test_accuracy/stats_table_test_accuracy_20_35_2_4.csv")
results_40_50_3_3<- read_csv("results_with_D=40,p=50,q=3,K=3.csv")
selected_40_50_3_3_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_50_3_3_test_accuracy <- results_40_50_3_3 %>%
select(selected_40_50_3_3_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_50_3_3_test_accuracy$Variable <- factor(
df_long_40_50_3_3_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_50_3_3<-ggplot(df_long_40_50_3_3_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=50,q=3,K=3",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_50_3_3.png",plot=plot_test_accuracy_40_50_3_3)
stats_table_test_accuracy_40_50_3_3 <- results_40_50_3_3 %>%
select(all_of(selected_40_50_3_3_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_50_3_3, "test_accuracy/stats_table_test_accuracy_40_50_3_3.csv")
results_40_50_2_3<- read_csv("results_with_D=40,p=50,q=2,K=3.csv")
selected_40_50_2_3_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_50_2_3_test_accuracy <- results_40_50_2_3 %>%
select(selected_40_50_2_3_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_50_2_3_test_accuracy$Variable <- factor(
df_long_40_50_2_3_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_50_2_3<-ggplot(df_long_40_50_2_3_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=50,q=2,K=3",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_50_2_3.png",plot=plot_test_accuracy_40_50_2_3)
stats_table_test_accuracy_40_50_2_3 <- results_40_50_2_3 %>%
select(all_of(selected_40_50_2_3_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_50_2_3, "test_accuracy/stats_table_test_accuracy_40_50_2_3.csv")
results_40_70_3_3<- read_csv("results_with_D=40,p=70,q=3,K=3.csv")
selected_40_70_3_3_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_70_3_3_test_accuracy <- results_40_70_3_3 %>%
select(selected_40_70_3_3_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_70_3_3_test_accuracy$Variable <- factor(
df_long_40_70_3_3_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_70_3_3<-ggplot(df_long_40_70_3_3_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=70,q=3,K=3",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_70_3_3.png",plot=plot_test_accuracy_40_70_3_3)
stats_table_test_accuracy_40_70_3_3 <- results_40_70_3_3 %>%
select(all_of(selected_40_70_3_3_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_70_3_3, "test_accuracy/stats_table_test_accuracy_40_70_3_3.csv")
results_40_70_2_3<- read_csv("results_with_D=40,p=70,q=2,K=3.csv")
selected_40_70_2_3_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_70_2_3_test_accuracy <- results_40_70_2_3 %>%
select(selected_40_70_2_3_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_70_2_3_test_accuracy$Variable <- factor(
df_long_40_70_2_3_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_70_2_3<-ggplot(df_long_40_70_2_3_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=70,q=2,K=3",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_70_2_3.png",plot=plot_test_accuracy_40_70_2_3)
stats_table_test_accuracy_40_70_2_3 <- results_40_70_2_3 %>%
select(all_of(selected_40_70_2_3_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_70_2_3, "test_accuracy/stats_table_test_accuracy_40_70_2_3.csv")
results_40_50_3_4<- read_csv("results_with_D=40,p=50,q=3,K=4.csv")
selected_40_50_3_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_50_3_4_test_accuracy <- results_40_50_3_4 %>%
select(selected_40_50_3_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_50_3_4_test_accuracy$Variable <- factor(
df_long_40_50_3_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_50_3_4<-ggplot(df_long_40_50_3_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=50,q=3,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_50_3_4.png",plot=plot_test_accuracy_40_50_3_4)
stats_table_test_accuracy_40_50_3_4 <- results_40_50_3_4 %>%
select(all_of(selected_40_50_3_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_50_3_4, "test_accuracy/stats_table_test_accuracy_40_50_3_4.csv")
results_40_50_2_4<- read_csv("results_with_D=40,p=50,q=2,K=4.csv")
selected_40_50_2_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_50_2_4_test_accuracy <- results_40_50_2_4 %>%
select(selected_40_50_2_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_50_2_4_test_accuracy$Variable <- factor(
df_long_40_50_2_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_50_2_4<-ggplot(df_long_40_50_2_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=50,q=2,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_50_2_4.png",plot=plot_test_accuracy_40_50_2_4)
stats_table_test_accuracy_40_50_2_4 <- results_40_50_2_4 %>%
select(all_of(selected_40_50_2_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_50_2_4, "test_accuracy/stats_table_test_accuracy_40_50_2_4.csv")
results_40_35_3_4<- read_csv("results_with_D=40,p=35,q=3,K=4.csv")
selected_40_35_3_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_35_3_4_test_accuracy <- results_40_35_3_4 %>%
select(selected_40_35_3_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_35_3_4_test_accuracy$Variable <- factor(
df_long_40_35_3_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_35_3_4<-ggplot(df_long_40_35_3_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=35,q=3,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_35_3_4.png",plot=plot_test_accuracy_40_35_3_4)
stats_table_test_accuracy_40_35_3_4 <- results_40_35_3_4 %>%
select(all_of(selected_40_35_3_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_35_3_4, "test_accuracy/stats_table_test_accuracy_40_35_3_4.csv")
results_40_35_2_4<- read_csv("results_with_D=40,p=35,q=2,K=4.csv")
selected_40_35_2_4_test_accuracy <- c("best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy","best_test_accuracy")
df_long_40_35_2_4_test_accuracy <- results_40_35_2_4 %>%
select(selected_40_35_2_4_test_accuracy) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
)
df_long_40_35_2_4_test_accuracy$Variable <- factor(
df_long_40_35_2_4_test_accuracy$Variable,
levels = c("best_test_accuracy", "best_SEM_test_accuracy", "best_SEMK_test_accuracy", "best_SKM_test_accuracy")
)
plot_test_accuracy_40_35_2_4<-ggplot(df_long_40_35_2_4_test_accuracy, aes(x = Variable, y = Value)) +
geom_boxplot(fill = "skyblue", alpha = 0.7) +
labs(title = "D=40,p=35,q=2,K=4",
x="Classification accuracy",
y = "") +
theme_minimal()+
theme(
plot.title = element_text(size = 40, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 30),
axis.title.y = element_text(size = 30),
axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.line = element_line(color = "black"),
panel.border = element_rect(color = "black", fill = NA)
)+
scale_x_discrete(labels = c("GSAKM", "SEM", "SEMK", "SKM"))
ggsave("test_accuracy/Plot_test_accuracy_40_35_2_4.png",plot=plot_test_accuracy_40_35_2_4)
stats_table_test_accuracy_40_35_2_4 <- results_40_35_2_4 %>%
select(all_of(selected_40_35_2_4_test_accuracy)) %>%
pivot_longer(
everything(),
names_to = "Variable",
values_to = "Value"
) %>%
group_by(Variable) %>%
summarise(
`Mean` = mean(Value, na.rm = TRUE),
`SD` = sd(Value, na.rm = TRUE),
.groups = "drop"
)
write_csv(stats_table_test_accuracy_40_35_2_4, "test_accuracy/stats_table_test_accuracy_40_35_2_4.csv")
renv::update()
renv::clean()
renv::snapshot()
