如何解决如何使用'caret'库将数据加载到R中？
我正在尝试使用'插入符'库评估R中的多个交叉验证预测模型，但是每次尝试加载数据集时都会出现一条错误消息。我知道我做错了，但是看不到错误（我总结了下面的代码）：
> ticData<-read.table("tic-tac-toe.data.txt",header=F,sep=',')
> ticData
V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
1 x x x x o o x o o positive
2 x x x x o o o x o positive
3 x x x x o o o o x positive
4 x x x x o o o b b positive
5 x x x x o o b o b positive
6 x x x x o o b b o positive
[…]
> colnames(ticData) <- c("topl","topm","topr","midl","midm","midr","botl","botm","botr","class")
> head(ticData)
topl topm topr midl midm midr botl botm botr class
1 x x x x o o x o o positive
2 x x x x o o o x o positive
3 x x x x o o o o x positive
4 x x x x o o o b b positive
5 x x x x o o b o b positive
6 x x x x o o b b o positive
> complete.cases("tic-tac-toe.data")
[1] TRUE
> library(caret)
Loading required package: lattice
Loading required package: ggplot2
> set.seed(100)
> trainIndex <- createDataPartition(ticData$class,p=0.7,list=FALSE,times=1)
> head(trainIndex)
Resample1
[1,] 1
[2,] 2
[3,] 4
[4,] 6
[5,] 7
[6,] 9
> Train <- ticData[ trainIndex,]
> Test <- ticData[-trainIndex,]
> install.packages("klaR")
> install.packages("C50")
> install.packages("nnet")
> install.packages("kernlab")
> library(caret)
> ticData$class=as.factor(ticData$class)
> head(ticData)
topl topm topr midl midm midr botl botm botr class
1 x x x x o o x o o positive
2 x x x x o o o x o positive
3 x x x x o o o o x positive
4 x x x x o o o b b positive
5 x x x x o o b o b positive
6 x x x x o o b b o positive
> fitControl<-trainControl(
+ method="nb",+ number=10)
> set.seed(100)
> nbFit<-train(class~.,data=ticData,+ method="nb",+ trControl=fitControl,+ verbose=FALSE)
Error: Not a recognized resampling method.
我还在学习，在此先多谢：）
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