Question

我正在尝试使用foreach包运行随机林进行并行处理。这是我正在运行的代码。

library(doParallel)
library(doMC)
library(foreach)
library(randomForest)

Train <- read.csv("Train_Parallel.csv")
Test <- read.csv("Test_Parallel.csv")
Scoring <- read.csv("Scoring_Parallel.csv")


cores = detectCores()-1
cl = makeCluster(cores)
registerDoParallel(cl)

startparallel <- Sys.time()
rf_parallel <- foreach(ntree=rep(400, cores), .combine=combine, .multicombine=TRUE,
              .packages='randomForest') %dopar% {
                randomForest(target ~ .,
                             data=Train,
                             importance=TRUE,
                             ntree=ntree,
                             mtry = 25)
              }
endparallel <- Sys.time()
stopCluster(cl)
endparallel - startparallel

并行执行代码按预期运行。但是，当我针对我的训练和测试数据集运行预测函数时，我得到以下错误。我做错了什么？

> Train$Predicted <- predict(rf_parallel, Train)
Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class "list"
> Test$Predicted <- predict(rf_parallel, Test)
Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class "list"

Answer 1

确保randomForest :: combine未被dplyr :: combine或其他东西掩盖

对从并行处理创建的随机森林模型进行评分

1 个答案: