We will use the Ames Housing dataset, which has 82 variables and 2930 observations (AmesHousing.txt). The 82 features include 23 nominal, 23 ordinal, 14 discrete, and 20 continuous variables. You may just use 20 continuous variables in this project.

Your goal is to predict the sale price. \textbf{Exclude the Order, PID, and of course SalesPrice variables from your predictors.} You may want to combine variables (e.g. summing square feet) and perform transformations for addressing the nonlinearity that we have learned about.

You should try multiple linear regression (with or without transformations) and perform variable selection or shrinkage methods, but you are welcome to explore more! You need to preprocess the dataset. After the preprocessing, use the following code to define your test set, and its complement the training set.

I'm nit able to upload the txt file here.