Glance at the fit of your models

In this exercise you will use glance() to calculate how well the linear models fit the data for each country.

This exercise is part of the course

Machine Learning in the Tidyverse

Exercise instructions

Append a column (fit) containing the fit statistics for each model to the gap_models data frame and save it as model_perf_nested.
Simplify this data frame using unnest() to extract these fit statistics of each model and save it as model_perf.
Finally, use head() to take a peek at model_perf.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Extract the fit statistics of each model into data frames
model_perf_nested <- gap_models %>% 
    mutate(fit = map(model, ~___(.x)))

# Simplify the fit data frames for each model    
model_perf <- model_perf_nested %>% 
    unnest(___)
    
# Look at the first six rows of model_perf
head(___)

Edit and Run Code