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.
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.
# Train logistic model
logistic_fit <- ___ %>%
___(___, data = ___)