Classification I

Week 08, Fall 2023

Summary

This week we will introduce our second machine learning task: classification. After introducing the task, we will see how to re-use methods we have already learned to perform the task. This week, we will focus on on nonparametric classification techniques, in particular KNN and decision trees.

Learning Objectives

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

  • Differentiate between regression and classification tasks.
  • Estimate and calculate conditional probabilities.
  • Understand how conditional probabilities relate to classifications.
  • Use Python to fit KNN and decision tree models to make classifications or estimate conditional probabilities.
  • Calculate classification metrics such as accuracy and misclassification rate.
  • Select models by manipulating their flexibility through the use of a tuning parameter.
  • Avoid overfitting by selecting an a model of appropriate flexibility through the use of cross-validation.

Reading

Link Source
Week 08 Concept Scribbles Course Website
Week 08 Notebook [ Rendered Notebook ] Course Website

Video

Head to ClassTranscribe to watch lecture recordings. They are arranged by date in the Lecture Capture Recordings playlist.

Assignments

Assignment Deadline Credit
Lab 05 [ Template ] Thursday, October 19 100% / 105%
Homework 05 Thursday, October 19 105%

Office Hours

Staff Day Time Location
David Monday 11:00 AM - 12:00 PM 2328 Siebel Center
Lahari Wednesday 4:00 PM - 5:00 PM Siebel Center, Second Floor [ Queue ]
David Wednesday 5:00 PM - 6:00 PM Zoom
Eunice Thursday 3:00 PM - 4:00 PM Siebel Center, Second Floor [ Queue ]