Course Activities 
Week 1 (Jan 913) 
Read Chapter 1: Overview of Data Mining 
Lecture 1: Introduction 

Get Familiar with Software: Intrudction to R 
R Brief Intro, R Guide For Reginners 

Supplementary Reading: Data mining and statistics:
what is the connection? Friedman (1997) 
Homework 1.
Assigned on Jan 15, due on Jan 29. 
Week 23 (Jan 1427) 
Read Chapter 2: Theory of Supervised Learning 
Lecture 2: Statistical Decision Theory (I) 


Lecture 3: Statistical Decision Theory (II) 
Week 4 (Jan 28Feb 3) 
Read Chapter 4.24.4: Linear Classificaton Methods for Binary Problems 
Lecture 4: Binary Classification (I): Basics 


Homework 2 Assignment. Assigned on Jan 29, due on Feb 12. 
Week 6 (Feb 4  Feb 10) 
Supplementary Reading: Choosing Between Logistic Regression and Discriminant Analysis, Press, S. and Wilson, S. (1978) 
Lecture 5: Binary Classification (II): Logistic Regression and Discriminant Analysis 

Curse of Dimensionality; Linear Binary Classification for High Dimensional Problems 
Lecture 6: Binary Classification (III): Extension to High Dimensional Classification Problems 
Week 4 (Feb 11  Feb 17) 
Read Chapter 4.1: Nonlinear Classification Methods 
Lecture 7: K nearest neighbor (Knn) methods 

Topic: Introduction to Multiclass Classifiction 
Lecture 8: Multiclass Classification 


Homework 3 Assignment.Assigned on Feb 12, due on Feb 26 
Week 5 (Feb 18  Feb 24) 
Topic: Nonlinear Discriminant Analysis 
Lecture 9: QDA and RDA 

Supplementary Reading: LDA for improved large vocabulary continuous speech recognition 
Lecture 10: PCA 
Week 6 (Feb 25  March 3) 
Topic: Linear Regression Models 
Lecture 11: Linear Regression 

Read Chapter 3 : Linear Regression, Supplementary Reading: Linear Model Theory 
