6 Binary Classification

  • Start: Monday, March 1
  • End: Friday, March 5

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.

6.4 Video

Title Link Mirror
6.1 - Welcome to Week 06 6.1 - YouTube 6.1 - ClassTranscribe
6.2 - Logistic Regression 6.2 - YouTube 6.2 - ClassTranscribe
6.3 - Logistic Regression in R 6.3 - YouTube 6.3 - ClassTranscribe
6.4 - Binary Classification 6.4 - YouTube 6.4 - ClassTranscribe
6.5 - Binary Classification in R 6.5 - YouTube 6.4 - ClassTranscribe

6.5 Assignments

Assignment Deadline Credit
Exam 01 Monday, March 1 100%
Quiz 04 Monday, March 8 85%
Quiz 05 Monday, March 8 105%

6.6 Office Hours

Staff and Link Day Time
Zoom with David Thursday 8:00 PM - 9:00 PM
Zoom with Tianyi Thursday 9:00 PM - 10:00 PM
Piazza Any! Any!