Cross validation for glm() models

Question

I\'m trying to do a 10-fold cross validation for some glm models that I have built earlier in R. I\'m a little confused about the cv.glm() function in the boo

Answer 1

I am always a little cautious about using various packages 10-fold cross validation methods. I have my own simple script to create the test and training partitions manually for any machine learning package:

#Randomly shuffle the data
yourData<-yourData[sample(nrow(yourData)),]

#Create 10 equally size folds
folds <- cut(seq(1,nrow(yourData)),breaks=10,labels=FALSE)

#Perform 10 fold cross validation
for(i in 1:10){
    #Segement your data by fold using the which() function 
    testIndexes <- which(folds==i,arr.ind=TRUE)
    testData <- yourData[testIndexes, ]
    trainData <- yourData[-testIndexes, ]
    #Use test and train data partitions however you desire...
}