Serialize and restore Random Planted Forests — rpf

rpf_marshal() converts an rpf object into a plain R list safe for saveRDS(); rpf_unmarshal() reverses it. The C++ forest behind an rpf object does not survive R serialization, so this explicit round-trip is required to store or transfer fitted models.

Usage

rpf_marshal(x, include_data = FALSE)

rpf_unmarshal(blob)

Arguments

x: An object of class rpf.
include_data: [FALSE]: Store training data in the blob, enabling purify() after restoring.
blob: An object of class rpf_marshaled created by rpf_marshal().

Value

rpf_marshal() returns a list of class rpf_marshaled; rpf_unmarshal() returns an object of class rpf.

Details

Training data is only included with include_data = TRUE; without it, a restored forest can predict (including purified prediction if the forest was purified before marshaling) but can never be purified afterwards.

Examples

fit <- rpf(mpg ~ wt + cyl, data = mtcars, ntrees = 10)
blob <- rpf_marshal(fit)
tmp <- tempfile(fileext = ".rds")
saveRDS(blob, tmp)
restored <- rpf_unmarshal(readRDS(tmp))
all.equal(predict(fit, mtcars), predict(restored, mtcars))
#> [1] TRUE