We will try to predict per capita crime rate (crim) using other variablesavailable in the Boston data set of MASS library. Try out some of the model selectionmethods that we discussed in Chapter 6,...

We will try to predict per capita crime rate (crim) using other variablesavailable in the Boston data set of MASS library. Try out some of the model selectionmethods that we discussed in Chapter 6, namely best subset, ridge regression, the lasso,and PCR. Propose a final model (or a set of models) that seem to perform well on thisdata set, and justify your selection. Make sure that you are evaluating model performanceusing cross-validation (10-fold CV) as opposed to using training error.