Question

我使用的是R package 插入符号，并行处理不起作用。如果我尝试从train函数运行示例：

library(mlbench)
data(BostonHousing)

library(doMC)
registerDoMC(2)

## NOTE: don't run models form RWeka when using
### multicore. The session will crash.

## The code for train() does not change:
set.seed(1)
usingMC <-  train(medv ~ .,
                  data = BostonHousing, 
                  "glmboost")

我收到以下错误：

Error in names(resamples) <- gsub("^\\.", "", names(resamples)) : 
  attempt to set an attribute on NULL

我使用的是2011年初的MacBook Pro，配备2.3GHz Intel Core i5和Mac OS X 10.6.8。

R会话信息：

R版本2.13.0（2011-04-13）平台：   x86_64-apple-darwin9.8.0 / x86_64（64位）

附加基础包：[1] stats graphics grDevices utils
  数据集方法基础

其他附件包：[1] caret_5.13-20 cluster_1.14.2   reshape_0.8.4 plyr_1.7.1 lattice_0.19-33 mlbench_2.1-0
  doMC_1.2.3 multicore_0.1-7 [9] foreach_1.3.2 codetools_0.2-8   iterators_1.0.5

通过命名空间加载（而不是附加）：[1] compiler_2.13.0   grid_2.13.0 rpart_3.1-51 tools_2.13.0

我能做些什么来解决这个问题吗？

Answer 1

可能很难找到能够重现错误的人：

> sessionInfo ()
R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-linux-gnu (64-bit)

[...剪断...]

other attached packages:
 [1] mboost_2.1-2    caret_5.15-023  cluster_1.14.2  reshape_0.8.4  
 [5] plyr_1.7.1      lattice_0.20-6  doMC_1.2.5      multicore_0.1-7
 [9] iterators_1.0.6 foreach_1.4.0   mlbench_2.1-0          

loaded via a namespace (and not attached):
[1] codetools_0.2-8  compiler_2.15.0  grid_2.15.0      Matrix_1.0-6    
[5] splines_2.15.0   survival_2.36-14 tools_2.15.0

它有效。

这意味着您可能需要深入研究代码：traceback ()和debug ()应该有所帮助。

Answer 2

我至少在2.14.0上无法重现这个问题（见下文）。

插入符代码没有用于顺序和并行处理的不同版本，所以我不确定问题是什么。顺序版本是否有效？其他型号怎么样？你还可以尝试新的会议吗？

此外，您可能希望直接向软件包维护者发送电子邮件（除非您这样做，我错过了它）以获得更好的结果。

> library(caret)

＆LT; -snip-＆GT;

> library(mlbench)
> data(BostonHousing)
> 
> library(doMC)

＆LT; -snip-＆GT;

> registerDoMC(2)
> 
> ## NOTE: don't run models form RWeka when using
> ### multicore. The session will crash.
> 
> ## The code for train() does not change:
> set.seed(1)
> usingMC <-  train(medv ~ .,
+                   data = BostonHousing, 
+                   "glmboost")
Warning message:
In glmboost.matrix(x = c(0.00632, 0.02731, 0.02729, 0.03237, 0.06905,  :
  model with centered covariates does not contain intercept
> usingMC
506 samples
 13 predictors

No pre-processing
Resampling: Bootstrap (25 reps) 

Summary of sample sizes: 506, 506, 506, 506, 506, 506, ... 

Resampling results across tuning parameters:

  mstop  RMSE  Rsquared  RMSE SD  Rsquared SD
  50     5.44  0.663     0.484    0.0661     
  100    5.33  0.675     0.518    0.0669     
  150    5.27  0.681     0.526    0.0661     

Tuning parameter 'prune' was held constant at a value
 of 'no'
RMSE was used to select the optimal model using 
 the smallest value.
The final values used for the model were mstop = 150
 and prune = no. 
> sessionInfo()
R version 2.14.0 (2011-10-31)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets 
[6] methods   base     

other attached packages:
 [1] mboost_2.1-1    doMC_1.2.5      multicore_0.1-7
 [4] iterators_1.0.5 mlbench_2.1-0   caret_5.15-023 
 [7] foreach_1.4.0   cluster_1.14.1  reshape_0.8.4  
[10] plyr_1.7.1      lattice_0.20-0 

loaded via a namespace (and not attached):
[1] codetools_0.2-8  compiler_2.14.0  grid_2.14.0     
[4] Matrix_1.0-3     splines_2.14.0   survival_2.36-10
[7] tools_2.14.0

插入符号中的并行处理在R 2.13.0上不起作用

2 个答案: