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.
This exercise is part of the course
Modeling with tidymodels in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Set tuning hyperparameters
dt_tune_model <- decision_tree(___ = ___,
___ = ___,
___ = ___) %>%
# Specify engine
___ %>%
# Specify mode
___
dt_tune_model