How to find a split and root node in a regression tree, I made a regression tree from multiple vectors now I have to extract root node of rpart of multiple vectors.file contains numeric value of multiple vectors A,B,C,D,E,F,G,H ex. A vector contains 4,3,6,7,2,4,5,...and so on similarly others B,C,D,E,F,G,H .so want to extract F (which is a root node in my case) as an output from this input an after creating a tree .thank you.sorry unable to put any image :(
Here's what I've done so far
log_data <- read.csv(file="C:\\Users\\AASHU\\Desktop\\CART\\syn.csv",
header=T, as.is=T)
library(rpart)
fit <- rpart(A ~ B+C+D+E+F+G+H, log_data)
# plot(fit)
plot(fit, compress=TRUE, branch=0)
text(fit, xpd = NA, cex = 0.7)
summary(fit)
Call:
rpart(formula = A ~ B + C + D + E + F + G + H, data = log_data)
n=52 (1 observation deleted due to missingness)
CP nsplit rel error xerror xstd
1 0.09798662 0 1.0000000 1.065250 0.1888568
2 0.09347624 1 0.9020134 1.198999 0.1842667
3 0.03632980 2 0.8085371 1.154558 0.1859743
4 0.02297130 3 0.7722073 1.254874 0.2029423
5 0.01000000 4 0.7492360 1.274024 0.2118272
Node number 1: 52 observations, complexity param=0.09798662
mean=4.403846, MSE=1.509985
left son=2 (7 obs) right son=3 (45 obs)
Primary splits:
F < 5.5 to the right, improve=0.09798662, (0 missing)
...........
Now I have to extract root node F(F>=5.5) from fit (regression tree) and its split,can anyone help me?.
find the lables of that tree so that we can extract any of the vector
when the root node is character(ex.-A)
nodes<-labels(fit, digits=4, minlength=1L, pretty, collapse=TRUE)
root<-substr(nodes[2], 1, 1)
from the path we can extract the root node of a tree,below one is best to extract root node name by going through its second split which is nothing but an root node.
nodes<-labels(fit, digits=4, minlength=1L, pretty, collapse=TRUE)
path<-path.rpart(fit, node_no, pretty=0, print.it=FALSE)
path[[2]][1]
来源：https://stackoverflow.com/questions/13011496/splits-and-root-node-of-binary-decision-treecart