how to get all terminal nodes - weight & response prediction 'ctree' in r

Question

Here's what I can use to list weight for all terminal nodes : but how can I add some code to get response prediction as well as weight by each terminal node ID :

say I want my output to look like this

-- Here below is what I have so far to get the weight

nodes(airct, unique(where(airct))) 

Thank you

Answer 1

The Binary tree is a big S4 object, so sometimes it is difficult to extract the data.

But the plot method for BinaryTree object, hase an optional panel function of the form function(node) plotting the terminal nodes. So when you plot you can get all the informations about this node.

here I use the plot function, to extract the information and even better I usee the gridExtra and package to change the form of the terminal node as a table

library(party)
library(gridExtra)
set.seed(100)
lls <- data.frame(N = gl(3, 50, labels = c("A", "B", "C")), 
                  a = rnorm(150) + rep(c(1, 0,150)),
                  b = runif(150))
pond= sample(1:5,150,replace=TRUE)
tt <- ctree(formula=N~a+b, data=lls,weights = pond)
output.df <- data.frame()
innerWeights <- function(node){

 dat <- data.frame (x=node$nodeID,
                    y=sum(node$weights),
                    z=paste(round(node$prediction,2),collapse='  '))
  grid.table(dat,
             cols = c('ID','Weights','Prediction'),
             h.even.alpha=1, 
             h.odd.alpha=1,  
             v.even.alpha=0.5, 
             v.odd.alpha=1)
   output.df <<- rbind(output.df,dat)  # note the use of <<-

}

plot(tt, type='simple', terminal_panel = innerWeights)


data
  ID Weights       Prediction
1  4      24  0.42  0.5  0.08
2  5      17 0.06  0.24  0.71
3  6      24    0.08  0  0.92
4  7     388 0.37  0.37  0.26

Answer 2

Here's what I found , it works fine with a bit extra information. But I just want to post it here just in case someone need them in the future.

y <- do.call(rbind, nodes(tt, unique(where(tt))))
write.table(y, 'clipboard', sep='\t') 

@agstudy , let me know what you think.