orsf_time_to_train: Estimate training time

In aorsf: Accelerated Oblique Random Survival Forests

Estimate training time

Description

Estimate training time

Usage

orsf_time_to_train(object, n_tree_subset = 50)

Arguments

object	an untrained aorsf object
n_tree_subset	(integer) how many trees should be fit in order to estimate the time needed to train object. The default value is 50, as this usually gives a good enough approximation.

Value

a difftime object.

Examples

# specify but do not train the model by setting no_fit = TRUE.
object <- orsf(pbc_orsf, Surv(time, status) ~ . - id,
               n_tree = 500, no_fit = TRUE)

# grow 50 trees to approximate the time it will take to grow 500 trees
time_estimated <- orsf_time_to_train(object, n_tree_subset = 50)

print(time_estimated)

# let's see how close the approximation was
time_true_start <- Sys.time()
fit <- orsf_train(object)
time_true_stop <- Sys.time()

time_true <- time_true_stop - time_true_start

print(time_true)

# error
abs(time_true - time_estimated)

aorsf documentation built on Oct. 26, 2023, 5:08 p.m.