rpart: How to get the "where" vector for validation dataset?

Question

when fitting with rpart, it returns the "where" vector which tells which leave each record in the training dataset is on the tree. Is there a function which return something similar to this "where" vector for a test dataset?

not sure what you are asking, you want to get the subset for any node? https://stackoverflow.com/questions/36748531/getting-the-observations-in-a-rparts-node-i-e-cart — rawr, Mar 09 '18 at 17:37
Just something similar to the rpart$where vector of numbers, which tells which leave a record is on. But this is only for the training data. I wonder if I can get something similar for a test dataset. The predict function doesn't seem to do this, it only gives predicted values. — Meng zhao, Mar 09 '18 at 17:39

score 0 · Answer 1 · answered Mar 09 '18 at 18:09

I think the partykit package does what you want

library('rpart')
fit <- rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
fit
rpart.plot::rpart.plot(fit)

Check with same data

set.seed(1)
idx <- sample(nrow(kyphosis), 5L)
fit$where[idx]
# 22 30 46 71 16 
#  9  3  7  7  3 

library('partykit')
fit <- as.party(fit)
predict(fit, kyphosis[idx, ], type = 'node')
# 22 30 46 71 16 
#  9  3  7  7  3

Check with new data

dd <- kyphosis[idx, ]
set.seed(1)
dd[] <- lapply(dd, sample)
predict(fit, dd, type = 'node')
# 22 30 46 71 16 
#  5  3  7  9  3 

## so #46 should meet criteria for the 7th leaf:
with(kyphosis[46, ],
     Start  >= 8.5  &  # node 1
       Start < 14.5 &  # node 2
       Age  >= 55   &  # node 4
       Age  >= 111     # node 6
)
# [1] TRUE

Thanks for the reply. I tried, but it seems the only accepted values for 'type' are “vector”, “prob”, “class”, “matrix” — Meng zhao, Mar 09 '18 at 19:38

score 0 · Answer 2 · answered Aug 10 '18 at 00:32

As you mention, the function predict.rpart in the rpart package doesn't have a where option (to show the leaf node number associated with a prediction). However, the rpart.predict function in the rpart.plot package will do this. For example

> library(rpart.plot)
> fit <- rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
> rpart.predict(fit, newdata=kyphosis[1:3,], nn=TRUE)

gives (note the node number nn column):

   absent present nn
1 0.42105 0.57895  3
2 0.85714 0.14286 22
3 0.42105 0.57895  3

And

> rpart.predict(fit, newdata=kyphosis[1:3,], nn=TRUE)$nn

gives just the where node numbers:

[1]  3 22  3

To show the rule for each prediction use

> rpart.predict(fit, newdata=kyphosis[1:5,], rules=TRUE)

which gives

   absent present
1 0.42105 0.57895 because Start <  9
2 0.85714 0.14286 because Start is 9 to 15 & Age >= 111
3 0.42105 0.57895 because Start <  9

rpart: How to get the "where" vector for validation dataset?

2 Answers2