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  3. Modeling with Data in the Tidyverse

Exercise

Automating predictions on "new" houses

Let's now repeat what you did in the last exercise, but in an automated fashion assuming the information on these "new" houses is saved in a dataframe.

Your model for log10_price as a function of log10_size and the binary variable waterfront (model_price_4) is available in your workspace, and so is new_houses_2, a dataframe with data on 2 new houses. While not so beneficial with only 2 "new" houses, this will save a lot of work if you had 2000 "new" houses.

Instructions 1/2

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Apply get_regression_points() as you would normally, but with the newdata argument set to our two "new" houses. This returns predicted values for just those houses.