I am using the partial function to calculate two dimensional dependence. The code works fine. Unfortunately, when I add parallel computation commands, an error pops up. I have no idea how to solve it :(.
library(tidymodels)
library(doParallel)
#> Ładowanie wymaganego pakietu: foreach
#>
#> Dołączanie pakietu: 'foreach'
#> Następujące obiekty zostały zakryte z 'package:purrr':
#>
#> accumulate, when
#> Ładowanie wymaganego pakietu: iterators
#> Ładowanie wymaganego pakietu: parallel
library(pdp)
#>
#> Dołączanie pakietu: 'pdp'
#> Następujący obiekt został zakryty z 'package:purrr':
#>
#> partial
data("mtcars")
# tune:
workflow_fit <-
workflow() %>%
add_model(linear_reg() %>% set_engine("lm")) %>%
add_formula(mpg ~ wt + I(1/disp^2)) %>%
fit(data = mtcars)
# function pred.var:
pdp_pred_fun <- function(object, newdata) {
predict(object, newdata, type = "numeric")$.pred
}
# testing:
pdp_pred_fun(workflow_fit, mtcars[1:3,])
#> [1] 21.02471 20.37330 24.74476
# Why do not ?
cl <- makeCluster(4)
doParallel::registerDoParallel(cl)
workflow_partial <-
partial(workflow_fit,
pred.var = "disp",
pred.fun = pdp_pred_fun,
train = mtcars,
parallel = TRUE,
paropts = list(.packages = "earth"))
#> Error in {: task 1 failed - "niestosowalna metoda dla 'predict' zastosowana do obiektu klasy "workflow""
doParallel::stopImplicitCluster()
sessionInfo()
#> R version 4.2.1 (2022-06-23 ucrt)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 22000)
#>
#> Matrix products: default
#>
#> locale:
#> [1] LC_COLLATE=Polish_Poland.utf8 LC_CTYPE=Polish_Poland.utf8
#> [3] LC_MONETARY=Polish_Poland.utf8 LC_NUMERIC=C
#> [5] LC_TIME=Polish_Poland.utf8
#>
#> attached base packages:
#> [1] parallel stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] pdp_0.8.1 doParallel_1.0.17 iterators_1.0.14 foreach_1.5.2
#> [5] yardstick_1.1.0 workflowsets_1.0.0 workflows_1.0.0 tune_1.0.0
#> [9] tidyr_1.2.1 tibble_3.1.8 rsample_1.1.0 recipes_1.0.1
#> [13] purrr_0.3.4 parsnip_1.0.1 modeldata_1.0.1 infer_1.0.3
#> [17] ggplot2_3.3.6 dplyr_1.0.10 dials_1.0.0 scales_1.2.1
#> [21] broom_1.0.1 tidymodels_1.0.0
#>
#> loaded via a namespace (and not attached):
#> [1] splines_4.2.1 R.utils_2.12.0 prodlim_2019.11.13 assertthat_0.2.1
#> [5] highr_0.9 GPfit_1.0-8 yaml_2.3.5 globals_0.16.1
#> [9] ipred_0.9-13 pillar_1.8.1 backports_1.4.1 lattice_0.20-45
#> [13] glue_1.6.2 digest_0.6.29 hardhat_1.2.0 colorspace_2.0-3
#> [17] htmltools_0.5.3 Matrix_1.5-1 R.oo_1.25.0 timeDate_4021.104
#> [21] pkgconfig_2.0.3 lhs_1.1.5 DiceDesign_1.9 listenv_0.8.0
#> [25] gower_1.0.0 lava_1.6.10 styler_1.7.0 generics_0.1.3
#> [29] ellipsis_0.3.2 furrr_0.3.1 withr_2.5.0 nnet_7.3-17
#> [33] cli_3.4.0 survival_3.3-1 magrittr_2.0.3 evaluate_0.16
#> [37] R.methodsS3_1.8.2 fs_1.5.2 fansi_1.0.3 future_1.28.0
#> [41] parallelly_1.32.1 R.cache_0.16.0 MASS_7.3-57 class_7.3-20
#> [45] tools_4.2.1 lifecycle_1.0.2 stringr_1.4.1 munsell_0.5.0
#> [49] reprex_2.0.2 compiler_4.2.1 rlang_1.0.5 grid_4.2.1
#> [53] rstudioapi_0.14 rmarkdown_2.16 gtable_0.3.1 codetools_0.2-18
#> [57] DBI_1.1.3 R6_2.5.1 lubridate_1.8.0 knitr_1.40
#> [61] fastmap_1.1.0 future.apply_1.9.1 utf8_1.2.2 stringi_1.7.8
#> [65] Rcpp_1.0.9 vctrs_0.4.1 rpart_4.1.16 tidyselect_1.1.2
#> [69] xfun_0.33
