Model training and prediction
You have preprocessed your training and test datasets in the previous exercise. Since you incorporated feature engineering into your modeling workflow, you are able to use all of the predictor variables available in the telecommunications data!
The next step is training your logistic regression model and using it to obtain predictions on your new preprocessed test dataset.
Your preprocessed training and test datasets, telecom_training_prep and telecom_test_prep, as well as your model object, logistic_model, have been loaded into your session.
Questo esercizio fa parte del corso
Modeling with tidymodels in R
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Train logistic model
logistic_fit <- ___ %>%
___(___, data = ___)