Exercise

Crack the matrix

Visual representations are a great and intuitive way to assess results. One way to visualize and assess the performance of your model is by using a confusion matrix. In this exercise, you will create the confusion matrix of your predicted values to see in which cases it performs well and in which cases it doesn't.

The result of the previous exercise, predictions_combined, is still loaded.

Instructions 1/2

undefined XP

1

2

Calculate the confusion matrix of the predictions_combined tibble and save it as diabetes_matrix.
Print the result to the console.