Lecture15 - The Bayes classifier and k-nearest neighbors

• Lecture 15 Slides

Goals

• Additional notes on three optimization methods we have seen (gradient descent, coordinate descent, Newton-Raphson)

• Logistic regression diagnostics

• The Bayes Classifier

• k-nearest neighbors (kNN)

Required reading

• Chapter 4.1, 4.2, 4.3 in ISL

• Chapter 4.4 in ESL

• Deviance: appeared in Page 228 of ISL (very brief explanation)

• analysis of deviance: appeared in 4.4.2 of ESL

• The Bayes Classifier: Chapter 2.2.3 in ISL or Chapter 2.4 in ESL

• k-Nearest Neighbors: 4.7.6 in ISL or 13.3 in ESL

Suggested reading

• more about deviance in Chapter 12 of Applied Linear Regression, Sanford Weisberg

• 13.4 in ESL