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[Bug]: xgboost in R #208
Description
Describe the bug
In R, when I set the learner to "regr.xgboost", I get the following error:
Error in y[] <- lapply(y, reallocate) :
ALTLIST classes must provide a Set_elt method [class: XGBAltrepPointerClass, pkg: xgboost]
My OS is macos and the xgboost package in R was installed via the R CMD INSTALL . instead of the CRAN.
Minimum reproducible code snippet
library(DoubleML)
library(mlr3)
library(mlr3learners)
library(data.table)
set.seed(2)
ml_g = lrn("regr.xgboost", nthread = 2)
ml_m = ml_g$clone()
obj_dml_data = make_plr_CCDDHNR2018(alpha = 0.5)
dml_plr_obj = DoubleMLPLR$new(obj_dml_data, ml_g, ml_m)
dml_plr_obj$fit()
dml_plr_obj$summary()
Expected Result
dml_plr_obj$fit()
Actual Result
Error in y[] <- lapply(y, reallocate) :
ALTLIST classes must provide a Set_elt method [class: XGBAltrepPointerClass, pkg: xgboost]
Versions
sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.1.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Asia/Shanghai
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.4.2 tools_4.4.2
packageVersion('DoubleML')
[1] ‘1.0.1’
packageVersion('mlr3')
[1] ‘0.22.1’
packageVersion('xgboost')
[1] ‘2.1.2.1’
Activity
PhilippBach commentedon Nov 29, 2024
Hi @Forwardlee0 ,
thanks! As you probably guessed, I cannot replicate it locally (Windows, using xgboost from CRAN) ..
Have you tried to update the
mlr3andmlr3learnerspackages recently? I am not sure, but they issued some new releases which also crashed some of our checks, so maybe it's worth a try?What happens if you use the CRAN version of xgboost?
Forwardlee0 commentedon Nov 29, 2024
In Windows, there is no problem with the implementation of "regr.xgboost". The reason why I use xgboost from github instead of cran is that for xgboost of R in macos, xgboost from github can implement parallel computing, but cran's xgboost cannot. In addition, using xgboost from github alone for regression analysis is no problem. The above error occurs only when xgboost is implemented in doubleml.
Forwardlee0 commentedon Nov 29, 2024
All of the packages is the latest
Forwardlee0 commentedon Nov 29, 2024
I implement the following code, it works well:
library(mlr3)
library(mlr3learners)
library(data.table)
task = tsk("mtcars")
task$col_roles$target = "mpg"
learner = lrn("regr.xgboost")
learner$train(task)
prediction = learner$predict(task)
print(prediction)