Streamlining the modeling process
The last_fit()
function is designed to streamline the modeling workflow in tidymodels
. Instead of training your model on the training data and building a results tibble using the test data, last_fit()
accomplishes this with one function.
In this exercise, you will train the same logistic regression model as you fit in the previous exercises, except with the last_fit()
function.
Your data split object, telecom_split
, and model specification, logistic_model
, have been loaded into your session.
This exercise is part of the course
Modeling with tidymodels in R
Exercise instructions
- Pass your
logistic_model
object into thelast_fit()
function. - Predict
canceled_service
usingavg_call_mins
,avg_intl_mins
, andmonthly_charges
. - Display the performance metrics of your trained model,
telecom_last_fit
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Train model with last_fit()
telecom_last_fit <- ___ %>%
last_fit(___,
split = ___)
# View test set metrics
telecom_last_fit %>%
___