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rdecision-treerpart

export rpart rules to a data frame and link rules to train data

I have trained some data with rpart and interested in labeling each observation with the tree terminal node, and link to the rule corresponding to that terminal node.

I have used the following code as example:

library(rpart)
library(rattle)
fit <- rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
table(fit$where)
rattle::asRules(fit)

I'm able to label each observation via fit$where, the labels are:

> table(fit$where)

 3  5  7  8  9 
29 12 14  7 19

first question: these labels does not correspond with the labels generated by rattle::asRules(fit), which are 3,23,22,10,4 how can I generate the mapping table between the two?

second question: asRules just prints while I would like to put the rules in a table and not standard output.

my expected results: a data frame with a mapping between fit$where and asRules labels and another column with the rule text as a string, e.g.:

 Rule number: 4 [Kyphosis=absent cover=29 (36%) prob=0.00]
   Start>=8.5
   Start>=14.5

if we can parse the text to ID, statistics and condition in separate columns, even better but not mandatory.

I have found many related questions and links, but did not find a final answer.

thanks much, Kamashay

progress update 29/01

I'm able to extract each rule separately if I have the rule ID, via path.rpart:

>path.rpart(fit,node=22) 

 node number: 22 
   root
   Start>=8.5
   Start< 14.5
   Age>=55
   Age>=111

this gets me the rule as a list I can convert to a string. however the IDs are complaint with 'asRules' function and not 'fit$where'...

using "partykit" gets me the same results as "fit$where":

library("partykit")
> table(predict(as.party(fit), type = "node"))

 3  5  7  8  9 
29 12 14  7 19

so, I'm still not able to link between the two ( asRules IDs and fit$where IDs), I'm probably missing something fundamental, or there's a more straightforward way to do the task.

can you aid?

Solution

  • You can find the rule number (in fact the leaf node number) corresponding to each fit$where using

    > row.names(fit$frame)[fit$where]
 [1] "3"  "22" "3"  "3"  "4"  "4"  ...

    You might get a little closer to your desired output with

    > rattle::asRules(fit, TRUE)
R  3 [23%,0.58] Start< 8.5
R 23 [ 9%,0.57] Start>=8.5 Start< 14.5 Age>=55 Age< 111
...