5 fold Cross-validation

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I have used this code to perform a 5 fold cross-validation on the Davis dataset found in the carData library.

install.packages("caret")
library(caret)
trainControl<-trainControl(method="cv",number=5)
lm<-train(weight~height+repht+repwt,Davis,method="lm",trControl=trainControl)
lm

Running this I obtain the error saying that there are missing values for weight. This is the error message:

Error in na.fail.default(list(weight = c(77L, 58L, 53L, 68L, 59L, 76L, : missing values in object

I would be very grateful for any suggestions on how to solve this problem. Thanks in advance!

r-caret cross-validation r
1 Answers

You have missing errors in your predictor, so for example:

library(caret)
data = mtcars
data$mpg[c(3,6,9)]<-NA
trainControl<-trainControl(method="cv",number=5)
fit<-train(mpg~cyl+hp,data,method="lm",trControl=trainControl)

Error in na.fail.default(list(mpg = c(21, 21, NA, 21.4, 18.7, NA, 14.3,  : 
  missing values in object

Use complete.cases to get data that contains complete observations

complete.obs = complete.cases(data[,c("mpg","cyl","hp")])
data = data[complete.obs,]
fit<-train(mpg~cyl+hp,data,method="lm",trControl=trainControl)

In your case, it should be:

complete.obs = Davis[,c("weight","height","repht","repwt")]
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