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
How to Cite
Liang, J. (2022). Confusion Matrix: Machine Learning. POGIL Activity Clearinghouse, 3(4). Retrieved from https://pac.pogil.org/index.php/pac/article/view/304
CS-POGIL Activity Writing Program
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