I have a parsnip model (from ranger), roughly from here:
# install.packages("tidymodels")
data(cells, package = "modeldata")
rf_mod <-
rand_forest(trees = 100) %>%
set_engine("ranger") %>%
set_mode("classification")
set.seed(123)
cell_split <- initial_split(cells %>% select(-case), strata = class)
cell_train <- training(cell_split)
rf_fit <-
rf_mod %>%
fit(class ~ ., data = cell_train)
> class(rf_fit)
[1] "_ranger" "model_fit"
How do I save it to disk so that I can load it at a later time?
I tried dput, and that gets an error:
dput(rf_fit, file="rf_fit.R")
rf_fit2 <- dget("rf_fit.R")
Error in missing_arg() : could not find function "missing_arg"
It's true, the model_fit.R file has a couple of missing_arg calls in it, which appears to be some sort of way to mark missing args. However, that's a side line. I don't need to use dput, I just want to be able to save and load a model.
Try with this option. save() and load() functions allow you to store the model and then inkove it again. Here the code:
data(cells, package = "modeldata")
rf_mod <-
rand_forest(trees = 100) %>%
set_engine("ranger") %>%
set_mode("classification")
set.seed(123)
cell_split <- initial_split(cells %>% select(-case), strata = class)
cell_train <- training(cell_split)
rf_fit <-
rf_mod %>%
fit(class ~ ., data = cell_train)
#Export option
save(rf_fit,file='Mymod.RData')
load('Mymod.RData')
The other option would be using saveRDS() to save the model and then use readRDS() to load it but it requires to be allocated in an object:
#Export option 2
saveRDS(rf_fit, file = "Mymod.rds")
# Restore the object
rf_fit <- readRDS(file = "Mymod.rds")