problems with cross validation code - r - - r

Question

I'm writing a function to perform logistic regression on two columns of a dataframe. I can't get around the errors... I am trying to use 10-fold cross validation. Here's the code I'm using:
SAdata = read.table("http://statweb.stanford.edu/~tibs/ElemStatLearn/datasets/SAheart.data",
sep=",",head=T,row.names=1)
log.fun = function(x,y) {
prediction = data.frame()
tset = data.frame()
dframe = cbind(x,y)
dframe = as.data.frame(dframe)
dframe$fold = sample(1:10, nrow(data), replace = TRUE)
list = 1:10
for (i in 1:10) {
train = subset(dframe, fold %in% list[-i])
test = subset(dframe, fold %in% c(i))
model = glm(x~y, data=train, family=binomial)
pred = as.data.frame(predict(model, test[,-1]))
prediction <- rbind(prediction, pred)
}
}
log.fun(SAdata$chd,SAdata$obesity)
The error I get is "Error in sample.int(length(x), size, replace, prob) :
invalid 'size' argument"
Any ideas?

Answer 1

This is kinda sub-optimal use of for loops and specially modelling... if you want to try some good models developing try the package 'caret'
If you still want to use that function here is a workaround
SAdata = read.table("http://statweb.stanford.edu/~tibs/ElemStatLearn/datasets/SAheart.data",sep=",",head=T,row.names=1)
log.fun=function(x,y){
prediction = data.frame()
tset=data.frame()
dframe=cbind(x,y)
dframe=as.data.frame(dframe)
dframe$fold = sample(1:10, nrow(dframe), replace = TRUE)
list = 1:10
results <- list()
for (i in 1:10) {
results[[paste0('Fold',i)]]$train <- subset(dframe, fold %in% list[-i])
results[[paste0('Fold',i)]]$test <- subset(dframe, fold %in% c(i))
results[[paste0('Fold',i)]]$model <- glm(x~y, data=results[[i]]$train, family=binomial)
results[[paste0('Fold',i)]]$pred <- as.data.frame(predict(results[[i]]$model, results[[i]]$test[,-1]))
results[[paste0('Fold',i)]]$prediction <- rbind(prediction, results[[i]]$pred)
}
results}
your_results<-log.fun(SAdata$chd,SAdata$obesity)
head(your_results$Fold1$prediction)
In fact you had some problems in the function 'sample' since you were specifying 'data' and that object did not exist ... I replace it for dframe and added some names to each part of your results.
Hope it helps