考虑到 parRF 中的 par 代表并行，来自 caret R 包的 parRF 不适用于具有多个核心的我，这非常具有讽刺意味。如果这是相关信息，我在 Windows 机器上。我检查过我正在使用最新的关于插入符号和 doParallel 的最好的。
我做了一个最小的例子，并在下面给出了结果。有任何想法吗？
源代码
library(caret)
library(doParallel)
trCtrl <- trainControl(
method = "repeatedcv"
, number = 2
, repeats = 5
, allowParallel = TRUE
)
# WORKS
registerDoParallel(1)
train(form = Species~., data=iris, trControl = trCtrl, method="parRF")
closeAllConnections()
# FAILS
registerDoParallel(2)
train(form = Species~., data=iris, trControl = trCtrl, method="parRF")
closeAllConnections()
输出
> library(caret)
> library(doParallel)
>
> trCtrl <- trainControl(
+ method = "repeatedcv"
+ , number = 2
+ , repeats = 5
+ , allowParallel = TRUE
+ )
>
>
> # WORKS
> registerDoParallel(1)
> train(form = Species~., data=iris, trControl = trCtrl, method="parRF")
Parallel Random Forest
150 samples
4 predictors
3 classes: 'setosa', 'versicolor', 'virginica'
... some more model output, works fine!
> closeAllConnections()
>
> # FAILS
> registerDoParallel(2)
> train(form = Species~., data=iris, trControl = trCtrl, method="parRF")
Error in train.default(x, y, weights = w, ...) :
final tuning parameters could not be determined
In addition: Warning messages:
1: In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo, :
There were missing values in resampled performance measures.
2: In train.default(x, y, weights = w, ...) :
missing values found in aggregated results
> closeAllConnections()
session 信息
> sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=German_Germany.1252
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] doParallel_1.0.8 iterators_1.0.7 foreach_1.4.2 e1071_1.6-3 randomForest_4.6-7 caret_6.0-30 ggplot2_1.0.0
[8] lattice_0.20-29
loaded via a namespace (and not attached):
[1] BradleyTerry2_1.0-4 brglm_0.5-9 car_2.0-20 class_7.3-10 codetools_0.2-8 colorspace_1.2-4
[7] compiler_3.1.0 digest_0.6.4 gnm_1.0-7 grid_3.1.0 gtable_0.1.2 gtools_3.4.1
[13] lme4_1.1-6 MASS_7.3-31 Matrix_1.1-3 minqa_1.2.3 munsell_0.4.2 nlme_3.1-117
[19] nnet_7.3-8 plyr_1.8.1 proto_0.3-10 qvcalc_0.8-8 Rcpp_0.11.2 RcppEigen_0.3.2.1.2
[25] relimp_1.0-3 reshape2_1.4 scales_0.2.4 splines_3.1.0 stringr_0.6.2 tcltk_3.1.0
[31] tools_3.1.0
更新
session 信息2:
R version 3.0.2 (2013-09-25)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 LC_MONETARY=German_Germany.1252
[4] LC_NUMERIC=C LC_TIME=German_Germany.1252
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] e1071_1.6-1 class_7.3-9 randomForest_4.6-7 doParallel_1.0.6 iterators_1.0.6
[6] caret_5.17-7 reshape2_1.2.2 plyr_1.8 lattice_0.20-24 foreach_1.4.1
[11] cluster_1.14.4
loaded via a namespace (and not attached):
[1] codetools_0.2-8 compiler_3.0.2 grid_3.0.2 stringr_0.6.2 tools_3.0.2
最佳答案
这显然是插入符号 6.0-30 中的一个错误，它是在 5.17-7 版本之后的某个时间引入的。这也是另一个更可能影响 Windows 用户的问题，因为 doParallel“mclapply 模式”有效，而“clusterApplyLB 模式”失败。
我已经运行了一些测试，似乎问题是由于集群工作器没有正确初始化以执行嵌套并行计算，因此您可以通过在调用“train”之前在集群工作器中加载 foreach 包来解决该错误”。为此，您需要显式创建集群对象，而不是让“registerDoParallel”函数为您创建它(它在 Windows 上这样做)。例如:
cl <- makePSOCKcluster(2)
clusterEvalQ(cl, library(foreach))
registerDoParallel(cl)
我将与 caret 的作者联系以讨论该问题的解决方案。
关于r - 插入符号上的 parRF 不适用于多个核心，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/24786089/