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  3. Hyperparameter Tuning in R

Exercise

Changing the number of hyperparameters to tune

When we examine the model object closely, we can see that caret already did some automatic hyperparameter tuning for us: train automatically creates a grid of tuning parameters. By default, if p is the number of tuning parameters, the grid size is 3^p. But we can also specify the number of different values to try for each hyperparameter.

The data has again been preloaded as bc_train_data. The libraries caret and tictoc have also been preloaded.

Instructions

100 XP
  • Test four different values for each hyperparameter with automatic tuning in caret.