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.
Bu egzersiz, kursun bir parçasıdır
Modeling with tidymodels in R
Uygulamalı etkileşimli egzersiz
Bu egzersizi bu örnek kodu tamamlayarak deneyin.
# Set tuning hyperparameters
dt_tune_model <- decision_tree(___ = ___,
___ = ___,
___ = ___) %>%
# Specify engine
___ %>%
# Specify mode
___
dt_tune_model