rpart

I have a purely categorical dataframe from the UCI machine learning database https://archive.ics.uci.edu/ml/datasets/Diabetes+130-US+hospitals+for+years+1999-2008 I am using rpart to form a decision tree based on a new category on whether patients return before 30 days (a new failed category). I am using the following parameters for my decision tree tree_model <- rpart(Failed ~ race + gender + age+ time_in_hospital+ medical_specialty + num_lab_procedures+ num_procedures+num_medications+number_outpatient+number_emergency+number_inpatient+number_diagnoses+max_glu_serum+ A1Cresult+metformin

I would like to make a regression tree like the one in the picture. The tree was done in Cubist but I don't have that program. I do use R and Python. It seems to differ from the R packages rpart or tree in that the end nodes are linear formulas rather than just the average value. Is there any way I can do this using R or some other free software? In the picture, NDVI, B1,B2, etc are variables. The image is from this website . Cubist is an R port of the Cubist GPL C code released by RuleQuest at http://rulequest.com/cubist-info.html . Using the example from help('cubist') and the original

I'm using rpart to make a decision tree. For example: fit <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) How do I read in the formula part from a text file and get it in a format that rpart likes? I've tried: predictor_variables <- c("Age", "Number", "Start") rpart_formula <- Kyphosis ~ parse(text=paste(predictor_variables, collapse="+")) fit <- rpart(rpart_formula, data=kyphosis) but I get an error: invalid type (expression) for variable 'parse(text = paste(predictor_variables, collapse = "+"))' How can I format rpart_formula so that rpart sees it correctly? Use as.formula : rpart

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)

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