Confusion Matrix

Machine Learning

Abstract

This activity focuses on the evaluation of binary classification models using confusion matrix. In model 1, students will learn the table of confusion, which organizes the prediction results in a 2 by 2 matrix. In model 2, students will summarize a group of evaluation quantities based on the confusion matrix, including precision, recall, FPR, and accuracy. Lastly, students will compare the difference between type I and type II errors.

This activity was developed with NSF support through IUSE-1626765. You may request access to this activity via the following link: IntroCS-POGIL Activity Writing Program. 

• Level: Undergraduate
• Setting: Classroom
• Activity Type: Learning Cycle
• Discipline: Computer Science
• Course: Machine Learning
• Keywords: model evaluation, confusion matrix, precision, recall, accuracy, FPR