Fall 2020 Course Syllabus: Math 680

Course Title:	Advanced Statistical Learning
Textbook:	The Elements of Statistical Learning: Data Mining, Inference, and Prediction, by Hastie, Tibshirani, and Friedman; Publisher: Springer; 2nd edition, 2009; ISBN: 978-0387848570.
Reference Books:	An Introduction to Statistical Learning: with Applications in R, by James, Witten, Hastie, and Tibshirani (2013), Springer.
Prerequisites:	Math 478 or Math 678, or permission by instructor

Course Outline
Date	Lecture	Chapter	Topic	Assignment
Week 1 9/1	1	Chapter 1	Overview and Introduction, Application Examples.
Week 2 9/8	2	Chapter 2	Overview of Supervised Learning: Statistical Decision Theory	Homework 1
Week 3 9/15	3	Chapter 4	Binary Classification (I): Basics Binary Classification (II): Logistic Regression, Discriminant Analysis
Week 4 9/22	4	Chapter 18 & 2	Binary Classification (III): Extension to High Dimensional Classification Problems Nonlinear Classification Methods: K-nearest neighbor (Knn) methods.	Homework 2
Week 5 9/29	5	Chapter 4	Multiclass Classifications
Week 6 10/6	6	Chapter 4	Nonlinear Discriminant Analysis (I): QDA and RDA	Homework 3
Week 7 10/13	7	Chapter 14.5 & 3	Nonlinear Discriminant Analysis (II):  PCA  Linear Regression Models
Week 8 10/20		Chapter 3	Variable Selection for Linear Regression  Shrinkage Methods by LASSO	Statistical Learning Project Homework 4
Week 9 10/27	8	Chapter 3 & 7	Beyond LASSO Model Selection and Assessment
Week 10 11/3	9	Chapter 4.5 & 12	Modern Classification vis Separating Hyperplanes Support Vector Machines	Homework 5
Week 11 11/10	10	Chapter 12	Multiclass Support Vector Machines  Optimization Programming
Week 12 11/17	11	Chapter 9 & 8.7	Tree-based Methods: Classification and Regression Trees Bagging	Homework 6
Week 13 11/24	12	Chapter 10	Boosting and Additive Trees Friday, Nov 27: Thanksgiving Recess
Week 14 12/1	13	Chapter 14	Cluster Analysis
Week 15 12/8			Students’ Project Presentation Friday, Dec. 11: Reading Day 1
Week 16 12/15			FINAL EXAM: Tuesday ~ December 15, 2020

IMPORTANT DATES
FIRST DAY OF SEMESTER	September 1, 2020
LAST DAY TO WITHDRAW	November 9, 2020
LAST DAY OF CLASSES	December 10, 2020
FINAL EXAM PERIOD	December 15 – 21, 2020

Grading Policy

Assignment Weighting		Tentative Grading Scale
Homework	30 %	A	90 -- 100
Project	35 %	B+	85 -- 90
Final Exam	35 %	B	80 -- 85
		C+	75 -- 80
		C	70 -- 75
		F	0 -- 70

Important Departmental and University Policies

• Academic Integrity Code is Strictly Enforced
• Prerequisites Requirements are Enforced
• Attendance is Required in Lower-Division Courses
• Exam Policies (No Make Up Exams and More)
• Cell Phone and Pager Use Prohibited in Class
• Drop Date (Nov. 9, 2020) is Strictly Observed
• Complete DMS Course Policies (math.njit.edu/students/undergraduate/policies_math)

Prepared by Prof. Wenge Guo, August 11, 2020