Get Decision Tree Rule/Path Pattern for Every Row of Predicted Dataset for Rpart/Ctree Package in R

Extracting Rpart rules to segment a dataset

Almost a year since question was posted, but could be of help to others. The observations' node assignments in the rpart tree are saved in tree$where:

library("rpart")    
airq <- airquality[complete.cases(airquality),]
tree <- rpart(Ozone ~ ., data = airq)
tree$where

Extracting list of the split of a lmtree object

Models of class lmtree inherit from party just like the output from ctree(). Hence, the same approaches that are discussed here on SO for ctree() output can also be applied to lmtree() output. Namely, you can use the (still unexported) .list.rules.party() function:

partykit:::.list.rules.party(tr)
##                        2                        3 
## "z <= 0.495593577856198"  "z > 0.495593577856198" 

For further adaptations see: also:

• ctree() - How to get the list of splitting conditions for each terminal node?
• Get decision tree rule/path pattern for every row of predicted dataset for rpart/ctree package in R

Properties and their values out of J48 tree (RWeka)

One way to do this is to convert the J48 object from RWeka to a party object from partykit. You just need to as as.party(res) and this does all the parsing for you and returns a structure that is easier to work with with standardized extractor functions etc.

In particular you can then use all advice given in other discussions about ctree objects etc. See

• How to extract the splitting rules for the terminal nodes of ctree()

• Get decision tree rule/path pattern for every row of predicted dataset for rpart/ctree package in R

• Identify all distinct variables within party ctree nodel

And I think the following should do at least part of what you want:

library("partykit")
pres <- as.party(res)
partykit:::.list.rules.party(pres)
##                                                                                  2 
##                                                               "Petal.Width <= 0.6" 
##                                                                                  5 
##                     "Petal.Width > 0.6 & Petal.Width <= 1.7 & Petal.Length <= 4.9" 
##                                                                                  7 
## "Petal.Width > 0.6 & Petal.Width <= 1.7 & Petal.Length > 4.9 & Petal.Width <= 1.5" 
##                                                                                  8 
##  "Petal.Width > 0.6 & Petal.Width <= 1.7 & Petal.Length > 4.9 & Petal.Width > 1.5" 
##                                                                                  9 
##                                            "Petal.Width > 0.6 & Petal.Width > 1.7" 

Update: The OP contacted me off-list for a related question, asking for a specific printed representation of the tree. I'm including my solution here in case it is useful for someone else.

He wanted to have ( ) symbols signalling the hierarchy levels plus the names of the splitting variables. One way to do so would be to (1) extract variable names of the underlying data:

nam <- names(pres$data)

(2) Turn the recursive node structure of the tree into a flat list (which is somewhat more convenient for constructing the desired string):

tr <- as.list(pres$node)

(3a) Initialize the string:

str <- "("

(3b) Recursively add brackets and/or variable names to the string:

update_str <- function(x) {
   if(is.null(x$kids)) {
     str <<- paste(str, ")")
   } else {
     str <<- paste(str, nam[x$split$varid], "(")
     for(i in x$kids) update_str(tr[[i]])
   }
}

(3c) Call the recursion, starting from the root node:

update_str(tr[[1]])
str
## [1] "( Petal.Width ( ) Petal.Width ( Petal.Length ( ) Petal.Width ( ) ) )"

Using rpart Package in R, error selecting all variables for decision tree model

It seemed to be the \ in one of the variable names.

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