####R语言 随机森林 变量重要性可视化

install.packages("randomForest") 
install.packages("tidyverse") 


library(randomForest) 
library(tidyverse) 
install.packages("devtools")

library(conflicted)
library(dplyr)
filter(mtcars, cyl == 8)
dplyr::filter(mtcars, am & cyl == 8)
library(dplyr)
conflict_scout()

data("mtcars")
?mtcars
View(mtcars)

# 数据预处理
mtcars = mtcars %>%
  mutate(vs = as.factor(vs),
         am = as.factor(am) ,
         vs = fct_recode(vs,
                         'V-shaped'='0' ,
                         'straight'='1'),
         am = fct_recode(am,
                         "automatic'='0' ,
                          'manual'='1' ))

#构建随机森林
set.seed(1)
RF = randomForest(mpg~.,data = mtcars)

#可视化变量重要性
RF$importance %>%
       as.data.frame()  %>%
       rownames_to_column(var = 'Predictor&#