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.

Deze oefening maakt deel uit van de cursus

Modeling with tidymodels in R

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Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Create a confusion matrix
conf_mat(___,
         truth = ___,
         estimate = ___) %>% 
  # Create a heat map
  ___(type = ___)

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