1. Learn
    2. /
  2. Courses
    3. /
  3. Machine Learning in the Tidyverse
Connected

Exercise

Augmenting your data

From the results of glance(), you learned that using the available features the linear model fits well with an adjusted \(R^2\) of 0.99. The augment() function can help you explore this fit by appending the predictions to the original data.

Here you will leverage this to compare the predicted values of life_expectancy with the original ones based on the year feature.

Instructions

100 XP
  • Build the augmented data frame algeria_fitted using augment().
  • Visualize the fit of the model with respect to year by plotting both life_expectancy as points and .fitted as a line.