小编Jos*_*lma的帖子

我一直在尝试使用插入包来应用递归功能选择.我需要的是ref使用AUC作为性能测量.谷歌搜索了一个月后,我无法使该过程正常工作.这是我用过的代码:

library(caret)
library(doMC)
registerDoMC(cores = 4)

data(mdrr)

subsets <- c(1:10)

ctrl <- rfeControl(functions=caretFuncs, 
                   method = "cv",
                   repeats =5, number = 10,
                   returnResamp="final", verbose = TRUE)

trainctrl <- trainControl(classProbs= TRUE)

caretFuncs$summary <- twoClassSummary

set.seed(326)

rf.profileROC.Radial <- rfe(mdrrDescr, mdrrClass, sizes=subsets,
                            rfeControl=ctrl,
                            method="svmRadial",
                            metric="ROC",
                            trControl=trainctrl)

执行此脚本时,我得到以下结果:

Recursive feature selection

Outer resampling method: Cross-Validation (10 fold) 

Resampling performance over subset size:

Variables Accuracy  Kappa AccuracySD KappaSD Selected
     1   0.7501 0.4796    0.04324 0.09491         
     2   0.7671 0.5168    0.05274 0.11037         
     3   0.7671 0.5167    0.04294 0.09043         
     4   0.7728 …