计算交叉验证的残差

Question

我正在尝试从随机森林交叉验证中计算残差。我正在使用响应变量＆＃34; Sales＆＃34;在这个数据集中。我想将残差放入支持向量机。我在R中使用Carseats数据集。到目前为止，这是我的代码：

set.seed (1)
library(ISLR)
data(Carseats)
head(Carseats)
 Sales CompPrice Income Advertising Population Price ShelveLoc
1  9.50       138     73          11        276   120       Bad
2 11.22       111     48          16        260    83      Good
3 10.06       113     35          10        269    80    Medium
4  7.40       117    100           4        466    97    Medium
5  4.15       141     64           3        340   128       Bad
6 10.81       124    113          13        501    72       Bad
 Age Education Urban  US sales
1  42        17   Yes Yes   Yes
2  65        10   Yes Yes   Yes
3  59        12   Yes Yes   Yes
4  55        14   Yes Yes   Yes
5  38        13   Yes  No   Yes
6  78        16    No Yes   Yes

##Random forest
#cross validation to pick best mtry from 3,5,10
library(randomForest)
cv.carseats = rfcv(trainx=Carseats[,-1],trainy=Carseats[,1],cv.fold=5,step=0.9)
cv.carseats
with(cv.carseats,plot(n.var,error.cv,type="o"))

#from the graph it would appear mtry=5 produces the lowest error

##SVM
library(e1071)

#cross validation to pick best gamma
tune.out=tune(svm,Sales~.,data=Carseats,gamma=c(0.01,0.1,1,10),
tunecontrol = tune.control(cross=5))

我将取代＆＃34; Sales＆＃34;在SVM中随机森林交叉验证的残差。我很难计算随机森林交叉验证中的残差。任何帮助是极大的赞赏！谢谢！