You have to first split the data set into training and test sets. You also have the option of using a cross-validation technique to further segment the data set into a composite of training and test sets within the data.
Then you have to implement a choice selection of the performance metrics like the following:
- Confusion matrix
- Accuracy
- Precision
- Recall or sensitivity
- Specificity
- F1 score
For the most part, you can use measures such as accuracy, confusion matrix, or F1 score. However, it’ll be critical for you to demonstrate that you understand the nuances of how each model can be measured by choosing the right performance measure to match the problem.