6.1 Summary

This week we will introduce a parametric method for classification, logistic regression. Because it is a method focused on modeling binary outcomes, we will also discuss binary classification in depth, in particular, metrics for evaluating binary classification models.

6.2 Learning Objectives

After completing this week, you are expected to be able to:

• Estimate and calculate conditional probabilities with logistic regression.
• Use the glm() function in R to fit logistic regressions.
• Understand the definitions of false positives, false negatives, and related metrics.
• Calculate metrics specific to binary classification.

6.3 Reading

6.4 Video

6.5 Assignments

6.6 Office Hours

6.7 Additional Information

• Wikipedia: Confusion Matrix
• Wikipedia: Sensitivity and Specificity
• Wikipedia: Precision and Recall
• Wikipedia: Positive and Negative Predictive Values