CD Real Estate specializes in residential real estate services in the state of California. To complement the experience and local market knowledge of its licensed realtors, CD Real Estate wants to develop an analytical tool to predict the value of real estate. The file calireal contains data on some census tracts in California. The variables in these data are listed in Problem 20.

Predict the individuals’ credit scores using a linear regression model with lasso regularization.

Set aside 50% of the data as a test set and use 50% of the data for training and validation.

a. Determine the value of the lasso regularization penalty that minimizes the RMSE in a validation procedure.

b. For the best-performing linear regression model identified in part (a), what is the RMSE on the test set?

c. What are the coefficient values for the variables? Does the lasso regularization remove any variables from the model?

Problem 20

CD Real Estate specializes in residential real estate services in the state of California. To complement the experience and local market knowledge of its licensed realtors, CD Real Estate wants to develop an analytical tool to predict the value of real estate. The file calireal contains data on some census tracts in California. The variables in these data are listed in the following table.

Predict the median house value using an individual regression tree. Set aside 50% of the data as a test set and use 50% of the data for training and validation.

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Variable Longitude Description Longitude in center of tract Latitude Age Latitude in center of tract Median age of housing Rooms Total number of rooms Bedrooms Total number of bedrooms Population Population of tract Households Number of households Income Value Median income Median house value of tract (in $1,000s)