R中的插入符号:设置allowParallel的核心数量? [英] Caret in R: Set number of cores for allowParallel?

问题描述

我正在使用R的插入符号包，并且在训练函数(火车)中使用了有效的allowParallel参数.但是，它使用了所有内核，并且由于培训是在本地PC上运行的，所以我宁愿为自己留一个内核，以便能够在培训模型的同时进行工作.有什么办法吗?

I am using R's caret package, and in the training function (train) I use the allowParallel Parameter, which works. However, it uses all of the cores, and since the training runs on my local PC I would rather leave one core for myself to be able to work while training models. Is there any way to do this?

从我收集的数据来看，似乎不同的模型类型可能会使用不同的并行化程序包.我正在Windows上工作，所以我想它没有使用doMC(我知道如何设置内核数...)

From what I've gathered it seems that different model types might use different parallelization packages. I am working on windows, so I guess it's not using doMC (where I know how to set the number of cores...)

推荐答案

因此，在进行了更多研究之后，我找到了一种使用所需内核数的方法:train可以选择直接指定与num.threads = 7(8个核中有7个)

So after more research, I found a way to use the number of cores I want: train has the option to directly specify the number of cores to use with num.threads = 7 (for 7 out of 8 cores)

rf_model<-train(Target~., data = df_tree_train, method = "ranger",
                trControl = trainControl(method = "oob"
                                       , verboseIter  = TRUE
                                       , allowParallel = TRUE
                                       , classProbs = TRUE
                )
                , verbose = T
                , tuneGrid = tuneGrid
                , num.trees = 50
                , num.threads = 7  # <- This one
)

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