# Check if the package exists. If it does not exist, download the package from CRAN
if("boot" %in% rownames(installed.packages(),) == FALSE) {install.packages("boot",repos="cran.stat.ucla.edu")}
library(boot)

# Read the value of K
kay = %Question.kfold%
  #print(kay)
  
  # Read the value of max degree of polynomial
  degree <- %Question.poldegree%
  #print(degree)
  
  # Read the data stream into R
  the.data <- read.Alteryx("#1",mode="data.frame")
names(the.data) <- sapply(names(the.data), function(x) gsub("\\.", "\\_", x))

# Get the user input and make sure the names are acceptable R names
name.y.var <- names(the.data)[1]
#print(name.y.var)
name.x.var <- names(the.data)[-1]
#print(name.x.var)

cv.error <- rep(0,degree)
degreeVector <- 1:degree
model.name <- 'glm.fit'

for (d in degreeVector){
  dep <- paste(paste(paste(paste('poly(',name.x.var,sep=''),',',sep=''),d,sep=''),')',sep='')
  the.formula <- paste(name.y.var, '~', dep)
  model.call <- paste(paste(model.name, ' <- glm(', the.formula, ', data = the.data', sep=""),')',sep='')
  eval(parse(text = model.call))
  cv.error[d] <- cv.glm(data = the.data,glm.fit,K=kay)$delta[1]
}
AlteryxGraph(1,width=2400, height=3000, res=300)
(p <- plot(degreeVector,cv.error, type = "l", col = "blue", xlab = "Model Complexity (Degree of Polynomial)"))
invisible(dev.off())