Extract Edgelist from RandomForest Model

Converts a randomForest model object into a network edgelist representation by extracting parent-child relationships from one or more trees in the forest. Each edge represents a split in the decision tree, with additional attributes including split variable, split point, and prediction values.

Usage

# S3 method for class 'randomForest'
edgelist(input_object, treenum = NULL, ...)

Arguments

input_object

A randomForest model object from the randomForest package

treenum

Integer vector of tree numbers to extract (default: NULL extracts all trees). Values must be between 1 and input_object$ntree.

...

Additional arguments (currently unused)

Value

A data.frame with the following columns:

from

Parent node index within the tree

to

Child node index (left or right daughter)

split_var

Numeric index of the variable used for splitting

split_point

Threshold value for the split

prediction

Prediction value at the child node

direction

Branch direction: "left" or "right"

treenum

Tree number within the forest

split_var_name

Character vector with human-readable variable names

Examples

if (requireNamespace("randomForest", quietly = TRUE)) {
  set.seed(12)
  rf_model <- randomForest::randomForest(
    Species ~ .,
    data = iris,
    ntree = 5,
    maxnodes = 10
  )

  # Extract all trees
  rf_edges <- edgelist(rf_model)
  head(rf_edges)

  # Extract specific trees
  rf_edges_1 <- edgelist(rf_model, treenum = 1)
  rf_edges_13 <- edgelist(rf_model, treenum = c(1, 3))
}