Evaluate a random forest model

Similar to the linear regression model, you will use the MAE metric to evaluate the performance of the random forest model.

Cet exercice fait partie du cours

Machine Learning in the Tidyverse

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Instructions

Calculate the MAE by comparing the actual with the predicted values for the validate data and assign it to the validate_mae column.
Print the validate_mae column (note how they vary).
Calculate the mean of this column.

Note: The actual values of the validate fold (validate_actual) has already been added to your cv_data data frame.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

library(ranger)

# Calculate validate MAE for each fold
cv_eval_rf <- cv_prep_rf %>% 
  mutate(validate_mae = map2_dbl(___, ___, ~mae(actual = .x, predicted = .y)))

# Print the validate_mae column
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# Calculate the mean of validate_mae column
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