讲解链接
R语言分类树，决策树
library(readxl)
data <- read_excel(path = 'D:\sj1.xlsx')
library(rpart)
dtree<-rpart(事故责任~.,data=data,method="class", parms=list(split="information"))
printcp(dtree)
print(dtree)
tree<-prune(dtree,cp=0.0125)
tree<-prune(dtree,cp=dtree$cptable[which.min(dtree$cptable[,"xerror"]),"CP"])
opar<-par(no.readonly = T)
par(mfrow=c(1,1))
library(rpart.plot)
# #png(file = "D:\tree1.png")
rpart.plot(dtree,
type = 2, extra = "auto",
under = FALSE, fallen.leaves = TRUE,
digits = 2, varlen = 0, faclen = 1, roundint = TRUE,
cex = 0.6, tweak = 1,
clip.facs = FALSE, clip.right.labs = TRUE,
snip = FALSE,box.palette = 'red' ,shadow.col = 0,)
# #rpart.plot(dtree,branch=1,type=2, fallen.leaves=T,cex=0.8, sub="剪枝前")
# #png(file = "D:\tree2.png")
# #rpart.plot(tree,branch=1, type=4,fallen.leaves=T,cex=0.8, sub="剪枝后")
# #par(opar)
# #dev.off()代码片
#R语言分类树，决策树 library(readxl) data <- read_excel(path = 'D:\个人文件\研究生论文\长三角\数据整合\data2019\数据回归一张表201920210526.xlsx') library(rpart) dtree<-rpart(耦合协调度~Variable2+Variable8+Variable14+Variable16+Variable20+Variable22+Variable32+Variable34+Variable40+Variable52+Variable54+Variable64+Variable106+Variable115+Variable116+Variable82+Variable86,data=data,method="class", parms=list(split="information")) printcp(dtree) print(dtree) tree<-prune(dtree,cp=0.0125) tree<-prune(dtree,cp=dtree$cptable[which.min(dtree$cptable[,"xerror"]),"CP"]) opar<-par(no.readonly = T) par(mfrow=c(1,1)) #library(rpart.plot) # #png(file = "D:\tree1.png") rpart.plot(dtree,type = 2, extra = "auto",under = FALSE, fallen.leaves = TRUE,digits = 2, varlen = 0, faclen = 1, roundint = TRUE,cex = 0.6, tweak = 1,clip.facs = FALSE, clip.right.labs = TRUE,snip = FALSE,box.palette = 'red' ,shadow.col = 0,) # #rpart.plot(dtree,branch=1,type=2, fallen.leaves=T,cex=0.8, sub="剪枝前") # #png(file = "D:\tree2.png") # #rpart.plot(tree,branch=1, type=4,fallen.leaves=T,cex=0.8, sub="剪枝后") # #par(opar) # #dev.off()代码片
