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remotes::install_github("mlr-org/mlr@0c8185963f13303e143d634dc5bcd199edb01442")
library(mlr)
library(ParamHelpers)
library(parallelMap)
library(magrittr)
inner <- makeResampleDesc("CV", iters = 2)
outer <- makeResampleDesc("CV", iters = 4)
lrn_xgboost <- makeLearner(
"regr.xgboost",
par.vals = list(
objective = "reg:linear",
eval_metric = "error"
)
)
tune.ctrl_xgboost <- makeTuneControlRandom(maxit = 5L)
ps_xgboost_filter <- makeParamSet(
makeIntegerParam("nrounds", lower = 10, upper = 600),
makeNumericParam("colsample_bytree", lower = 0.3, upper = 0.7),
makeNumericParam("subsample", lower = 0.25, upper = 1),
makeIntegerParam("max_depth", lower = 1, upper = 10),
makeNumericParam("gamma", lower = 0, upper = 10),
makeNumericParam("eta", lower = 0.001, upper = 0.6),
makeNumericParam("min_child_weight", lower = 0, upper = 20),
makeNumericParam("fw.perc", lower = 0, upper = 1)
)
filter_wrapper_xgboost_borda <- makeFilterWrapper(lrn_xgboost,
fw.method = "E-Borda", cache = TRUE,
fw.base.methods = c(
"FSelectorRcpp_information.gain",
"linear.correlation",
"praznik_MRMR", "praznik_CMIM",
"carscore"
),
more.args = list("FSelectorRcpp_information.gain" = list(equal = TRUE)) # FSelectorRcpp
)
filter_wrapper_xgboost_gain.ratio <- makeFilterWrapper(lrn_xgboost, fw.method = "FSelectorRcpp_gain.ratio", cache = TRUE, equal = TRUE)
filter_wrapper_xgboost_info.gain <- makeFilterWrapper(lrn_xgboost, fw.method = "FSelectorRcpp_information.gain", cache = TRUE, equal = TRUE)
filter_wrapper_xgboost_variance <- makeFilterWrapper(lrn_xgboost, fw.method = "variance", cache = TRUE)
filter_wrapper_xgboost_rank.cor <- makeFilterWrapper(lrn_xgboost, fw.method = "rank.correlation", cache = TRUE)
filter_wrapper_xgboost_linear.cor <- makeFilterWrapper(lrn_xgboost, fw.method = "linear.correlation", cache = TRUE)
filter_wrapper_xgboost_mrmr <- makeFilterWrapper(lrn_xgboost, fw.method = "praznik_MRMR", cache = TRUE)
filter_wrapper_xgboost_cmim <- makeFilterWrapper(lrn_xgboost, fw.method = "praznik_CMIM", cache = TRUE)
filter_wrapper_xgboost_carscore <- makeFilterWrapper(lrn_xgboost, fw.method = "carscore", cache = TRUE)
# XGBOOST -----------------------------------------------------------------
xgboost_borda <- makeTuneWrapper(filter_wrapper_xgboost_borda,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost,
show.info = TRUE, measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Borda")
xgboost_info.gain <- makeTuneWrapper(filter_wrapper_xgboost_info.gain,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Info Gain")
xgboost_gain.ratio <- makeTuneWrapper(filter_wrapper_xgboost_gain.ratio,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Gain Ratio")
xgboost_variance <- makeTuneWrapper(filter_wrapper_xgboost_variance,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Variance")
xgboost_rank.cor <- makeTuneWrapper(filter_wrapper_xgboost_rank.cor,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Spearman")
xgboost_linear.cor <- makeTuneWrapper(filter_wrapper_xgboost_linear.cor,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Pearson")
xgboost_mrmr <- makeTuneWrapper(filter_wrapper_xgboost_mrmr,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost MRMR")
xgboost_cmim <- makeTuneWrapper(filter_wrapper_xgboost_cmim,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost CMIM")
xgboost_carscore <- makeTuneWrapper(filter_wrapper_xgboost_carscore,
resampling = inner,
par.set = ps_xgboost_filter,
control = tune.ctrl_xgboost, show.info = TRUE,
measures = list(rmse)
) %>%
magrittr::inset("id", "XGBoost Car")
parallelStart(
mode = "multicore",
level = "mlr.resample",
cpus = 4
)
set.seed(12345)
learner_list = list(xgboost_carscore, xgboost_cmim,
xgboost_mrmr, xgboost_linear.cor, xgboost_gain.ratio,
xgboost_variance, xgboost_borda)
bh.task_cust = dropFeatures(bh.task, "chas")
task_list = list(bh.task_cust)
bmr <- benchmark(
learners = learner_list,
tasks = task_list,
models = FALSE,
keep.pred = TRUE,
resamplings = outer,
show.info = TRUE,
measures = list(rmse, timetrain)
)
parallelStop()
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