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

**undefined XP**

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.