tests/testthat/test-performance.R

#
#
#
# # grow ----
#
# microbenchmark::microbenchmark(
#  aorsf = orsf(flc, time + status ~ .,
#               n_thread = 0,
#               n_split = 10,
#               leaf_min_obs = 10),
#  rfsrc = randomForestSRC::rfsrc(Surv(time, status) ~ .,
#                                 data = flc,
#                                 nodesize = 10,
#                                 samptype = 'swr'),
#  times = 1
# )
#
# microbenchmark::microbenchmark(
#  aorsf = orsf(pbc,
#               time + status ~ .,
#               n_thread = 0,
#               n_split = 10,
#               leaf_min_obs = 10),
#  rfsrc = randomForestSRC::rfsrc(Surv(time, status) ~ .,
#                                 data = pbc,
#                                 nodesize = 10,
#                                 samptype = 'swr'),
#  ranger = ranger::ranger(Surv(time, status) ~ .,
#                          data = pbc,
#                          num.thread = 0,
#                          min.node.size = 10),
#  times = 10
# )
#
# # predict ----
# source("tests/testthat/setup.R")
#
# fit_orsf <- orsf(pbc, time + status ~ ., n_thread = 0, leaf_min_obs = 10)
#
# fit_rfsrc <- randomForestSRC::rfsrc(Surv(time, status) ~ .,
#                                     data = pbc,
#                                     nodesize = 10,
#                                     samptype = 'swr')
#
#
# microbenchmark::microbenchmark(
#  orsf = predict(fit_orsf, new_data = pbc),
#  rfsrc = predict(fit_rfsrc, newdata = pbc),
#  times = 50
# )
# #
# fit_orsf <- orsf(flc, time + status ~ ., n_thread = 0, leaf_min_obs = 10)
#
# fit_rfsrc <- randomForestSRC::rfsrc(Surv(time, status) ~ .,
#                                     data = flc,
#                                     nodesize = 10,
#                                     samptype = 'swr')
#
#
# microbenchmark::microbenchmark(
#  orsf = predict(fit_orsf, new_data = flc),
#  rfsrc = predict(fit_rfsrc, newdata = flc),
#  times = 3
# )

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