Plotting the confusion matrix
Calculating performance metrics with the yardstick package provides insight into how well a classification model is performing on the test dataset. Most yardstick functions return a single number that summarizes classification performance.
Many times, it is helpful to create visualizations of the confusion matrix to more easily communicate your results.
In this exercise, you will make a heat map and mosaic plot of the confusion matrix from your logistic regression model on the telecom_df dataset.
Your model results tibble, telecom_results, 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.
# Create a confusion matrix
conf_mat(___,
truth = ___,
estimate = ___) %>%
# Create a heat map
___(type = ___)