Programming Homework Help. WVU 5 & 10 Fold Cross Validation and Random Splitting with 1000 Splits Model
In the MinnLand dataset in the alr4 package, fit two possible models with log(acrePrice) or sqrt(acrePrice) as the response, use year as a factor as well. I want to better understand land prices and the drivers. Use methods to develop two possible candidate models and compare them using
#5 Fold Cross Validation
#10 Fold Cross Validation
#Random Splitting with 1000 splits.
I only want to use parallel computing where you can/need, and function writing where you can/need because there are 18,700 observations. Before starting this analysis remove ALL NA’s from the data using na.omit(MinnLand). In each of the above cases comment on the models you would select and how you came about that decision. I’m studying insights it may have on the land prices in Minnesota over this time frame.
