问题描述
cl <- makeCluster(detectCores()-1)
registerDoParallel(cl)
tmpp <- pdp::partial(rf_full,pred.var = c("Date","AREA"),plot = T,plot.engine = "ggplot2",parallel = T)
stopCluster(cl)
Error in summary.connection(connection) : invalid connection
如果有帮助,这里是错误信息的回溯如下:
16.
summary.connection(connection)
15.
summary(connection)
14.
serialize(data,node$con)
13.
sendData.soCKnode(con,list(type = type,data = value,tag = tag))
12.
sendData(con,tag = tag))
11.
postNode(con,"EXEC",list(fun = fun,args = args,return = return,tag = tag))
10.
sendCall(cl[[i]],fun,list(...))
9.
clusterCall(cl,workerInit,c.expr,exportenv,pkgname,packages,attachExportEnv)
8.
e$fun(obj,substitute(ex),parent.frame(),e$data)
7.
foreach::`%dopar%`(fe,do.ply(i))
6.
llply(.data = .data,.fun = .fun,...,.progress = .progress,.inform = .inform,.parallel = .parallel,.paropts = .paropts)
5.
ldply(.data = pieces,.paropts = .paropts,.id = .id)
4.
plyr::adply(pred.grid,.margins = 1,.progress = progress,.parallel = parallel,.paropts = paropts,.fun = function(x) { temp <- train temp[,pred.var] <- x ...
3.
getParDepReg(object,pred.var = pred.var,pred.grid = pred.grid,inv.link = inv.link,ice = ice,train = train,progress = progress,parallel = parallel,paropts = paropts,...)
2.
partial.default(rf_full,parallel = T,paropts = list(.packages = "randomForest"))
1.
pdp::partial(rf_full,paropts = list(.packages = "randomForest")
注意:我在使用这种方式并行化之前学习了我的 RF 并且它有效。
这是我的会话信息:
> sessionInfo()
R version 4.0.4 (2021-02-15)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
system code page: 1250
attached base packages:
[1] parallel stats graphics Grdevices datasets utils methods base
other attached packages:
[1] doParallel_1.0.16 iterators_1.0.13 foreach_1.5.1 ggpubr_0.4.0
[5] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.0 purrr_0.3.4
[9] readr_1.3.1 tidyr_1.1.0 tibble_3.0.4 ggplot2_3.3.2
[13] tidyverse_1.3.0 pdp_0.7.0 MLmetrics_1.1.1 rpart_4.1-15
[17] randomForest_4.6-14
loaded via a namespace (and not attached):
[1] httr_1.4.2 jsonlite_1.7.1 carData_3.0-4 modelr_0.1.8
[5] assertthat_0.2.1 blob_1.2.1 renv_0.12.3 cellranger_1.1.0
[9] yaml_2.2.1 pillar_1.4.6 backports_1.1.8 lattice_0.20-41
[13] glue_1.4.2 digest_0.6.27 ggsignif_0.6.0 rvest_0.3.6
[17] colorspace_1.4-1 plyr_1.8.6 cowplot_1.1.1 htmltools_0.5.1.1
[21] pkgconfig_2.0.3 broom_0.7.0 haven_2.3.1 bookdown_0.20
[25] scales_1.1.1 openxlsx_4.2.3 rio_0.5.16 farver_2.0.3
[29] generics_0.0.2 car_3.0-10 ellipsis_0.3.1 withr_2.3.0
[33] cli_2.1.0 magrittr_1.5 Crayon_1.3.4 readxl_1.3.1
[37] evaluate_0.14 fs_1.4.2 fansi_0.4.1 rstatix_0.6.0
[41] xml2_1.3.2 foreign_0.8-80 tools_4.0.4 data.table_1.13.6
[45] hms_0.5.3 lifecycle_0.2.0 munsell_0.5.0 reprex_0.3.0
[49] zip_2.1.1 compiler_4.0.4 tinytex_0.26 rlang_0.4.10
[53] grid_4.0.4 rstudioapi_0.11 labeling_0.4.2 rmarkdown_2.5
[57] codetools_0.2-16 gtable_0.3.0 abind_1.4-5 DBI_1.1.0
[61] curl_4.3 R6_2.4.1 gridExtra_2.3 lubridate_1.7.9
[65] knitr_1.30 stringi_1.4.6 Rcpp_1.0.5 vctrs_0.3.4
[69] dbplyr_1.4.4 tidyselect_1.1.0 xfun_0.18
解决方法
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