Week 8 - Naive Bayes
Learning Objectives
After today's class, you should be able to:
- Understand the probabilistic Naive Bayes algorithm for classification tasks, including how it models feature likelihoods using Bayes’ Theorem with a conditional independence assumption.
- Calculate probabilities, develop and implement Naive Bayes models in Python.
- Apply the Naive Bayes formula to manually calculate posterior class probabilities using prior and conditional probabilities.
Class Agenda
- Naive Bayes Slides
[5 min]Break (Optional)- Naive Bayes Python Tutorial
- In Class Time for HW3_Naive_Bayes
Task List
- Required Reading: Chapter 8 - The Naive Bayes Classifier
- Complete and Submit HW3_Naive_Bayes on Canvas.
- Complete and Submit PA3_Coffee_Customer_Classification on Canvas/Gradescope.