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.

Deze oefening maakt deel uit van de cursus

Machine Learning in the Tidyverse

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Oefeninstructies

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.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

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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