party

I have the following plot as you can see in the picture, Is there any way to see exact number of percentage in the leaf nodes? If you want to "see" the percentages, the easiest way is to make a table() of the terminal nodes vs. the response and then look at the conditional proportions. If you want to "see" the proportions in the barplot, then there was no possibility to do this up to now. However, I tweaked the node_barplot() function to accomodate this feature. So if you re-install the partykit package (successor of the party package) from R-Forge you can try it: install.packages("partykit",

I am using ctree function within party R package. I would like to idenfiy all predictors that are used within the tree in order to reduce the data.frame dimension used for further analyses. For example: library(ctree) data(ozone) myModel<-ctree(Ozone~., data=na.omit(airquality)) plot(myModel) I would like a function receiving myModel and returning Temp, Wind and Ozone You can try using this: getUsefulPredictors<-function(x){ flatTree<-unlist(x@tree) pred<-unique(flatTree[grepl("*variableName",names(flatTree))]) return(pred) } It flattens the trees and looks for the elements having variableName

Is there any way to change the title sizes of a ctree plot? Use the following variables to quickly set up a ctree plot a<-c(41, 45, 50, 50, 38, 42, 50, 43, 37, 22, 42, 48, 47, 48, 50, 47, 41, 50, 45, 45, 39, 45, 46, 48, 50, 47, 50, 21, 48, 50, 48, 48, 48, 46, 36, 38, 50, 39, 44, 44, 50, 49, 40, 48, 48, 45, 39, 40, 44, 39, 40, 44, 42, 39, 49, 50, 50, 48, 48, 47, 48, 47, 44, 41, 50, 47, 50, 41, 50, 44, 47, 50, 24, 40, 43, 37, 44, 32, 43, 42, 44, 38, 42, 45, 50, 47, 46, 43, 37, 47, 37, 45, 41, 50, 42, 32, 43, 48, 45, 45, 28, 44,38, 41, 45, 48, 48, 47 ,49, 16, 45, 50, 47, 50, 43, 49, 50) X1<-c(NA

Been trying to use the rpart.plot package to plot a ctree from the partykit library. The reason for this being that the default plot method is terrible when the tree is deep. In my case, my max_depth = 5 . I really enjoy rpart.plot 's output as it allows for deep trees to visually display better. How the output looks for a simple example: rpart library(partykit) library(rpart) library(rpart.plot) df_test <- cu.summary[complete.cases(cu.summary),] multi.class.model <- rpart(Reliability~., data = df_test) rpart.plot(multi.class.model) I would like to get this output from the partykit model using

I have a data set with 6 categorical variables with levels ranging from 5 to 28. I have obtained an output from ctree() (party package) with 17 terminal nodes. I have followed the inputs by @Galled from ctree() - How to get the list of splitting conditions for each terminal node? to arrive at my desired output. But, I'm getting the following error post running the code: Error in data.frame(ResulTable, Means, Counts) : arguments imply differing number of rows: 17, 2 I have tried adding this extra lines: ResulTable <- rbind(ResulTable, cbind(Node = Node, Path = Path2)) ResulTable$Node <-

I'm trying to use cforest function(R, party package). This's what I do to construct forest: library("party") set.seed(42) readingSkills.cf <- cforest(score ~ ., data = readingSkills, control = cforest_unbiased(mtry = 2, ntree = 50)) Then I want to print the first tree and I do party:::prettytree(readingSkills.cf@ensemble[[1]],names(readingSkills.cf@data@get("input"))) The result look like this 1) shoeSize <= 28.29018; criterion = 1, statistic = 89.711 2) age <= 6; criterion = 1, statistic = 48.324 3) age <= 5; criterion = 0.997, statistic = 8.917 4)* weights = 0 3) age > 5 5)* weights = 0 2)