Before a bank offers a home loan, it is critical to conduct a home appraisal. The appraisal confirms the validity of the sales price of the property for the bank.
You have been asked to build and train a regression model that estimates the price of a home, based on several factors including: square feet of home, square feet of lot, number of bedrooms, number of bathrooms, location, and so on. You have been provided data for the following variables:
|Unique ID for each customer.
|Sale date of the estate. This variable is to be excluded for this regression model.
|The property's sales price in dollars. Price is the variable that you are trying to predict.
|Number of bedrooms above basement level.
|Number of bathrooms above basement level.
|Above ground living area in square feet.
|Square foot measurement for all floors.
|Number of floors.
|Is there a waterfront on the property? Yes = 1/No=0
|Overall condition rating.
|Original property construction date (year).
What skills do you develop in this practice exercise?
In this practice exercise, you can perform the following tasks in SAP Analytics Cloud:
- Build a regression model.
- Train the regression model.
- Verify the output from the regression model.