Exercise

Setting model hyperparameters

Hyperparameter tuning is a method for fine-tuning the performance of your models. In most cases, the default hyperparameters values of parsnip model objects will not be the optimal values for maximizing model performance.

In this exercise, you will define a decision tree model with hyperparameters for tuning and create a tuning workflow object.

Your decision tree workflow object, loans_dt_wkfl, has been loaded into your session.

Instructions 1/2

undefined XP

1

2

Create a parsnip decision tree model and set all three of its hyperparameters for tuning.
Use the rpart engine.