ISQS 6347, Data and Text Mining

Spring 2010 Schedule  

Class meetings: S1 - MW 11:00a-12:20p, BA257; S2 - MW 3:30p-4:50p, LH007

 

Textbooks

 

SPB: Data Mining for Business Intelligence Galit Shmueli, Nitin R. Patel, Peter C. Bruce

TSK: Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, and Vipin Kumar

RG: Data Mining A Tutorial Based Primer, Richard Roiger, Michael Geatz

 

Date

Day

Contents

Readings

Exercises

Notes

13-Jan

Wed

Introduction

SPB1, TSK1, RG1

 

  

18-Jan

Mon

Martin Luther King Jr.s Day No class

 

 

20-Jan

Wed

Data mining fundamentals - Concepts

SPB2, RG2

HW1 (due 02/01)

 

25-Jan

Mon

Data mining fundamentals Using SAS Enterprise Miner

SPB3, TSK3

 

27-Jan

Wed

Classification modeling

SPB4, TSK4, RG4

 

 

1-Feb

Mon

Classification modeling

SPB7, TSK4, RG3

HW2 (due 02/10)

3-Feb

Wed

Exercise 1 (Decision tree)

SPB7, TSK4, RG3

 

8-Feb

Mon

Logistic regression

AAEM61-4, SPB8, RG10

 

10-Feb

Wed

Logistic regression

AAEM61-4, SPB8, RG10

 

 

15-Feb

Mon

Model Assessment

AAEM61-6

HW3 (optional, due 3/01)

17-Feb

Wed

Review (Classification modeling contest)

State 0: Project orientation

22-Feb

Mon

Midterm I

 

Decision tree, logistic regression, model assessment

24-Feb

Wed

Introduction to pattern discovery

AAEM61-8

HW4 (optional, due 3/10)

1-Mar

Mon

Pattern discovery (clustering)

AAEM61-8, TSK8

3-Mar

Wed

Exercise 2 (Clustering)

AAEM61-8, TSK8

 

8-Mar

Mon

Pattern discovery (Association analysis)

AAEM61-8, TSK6

 

10-Mar

Wed

Exercise 3 (association analysis)

AAEM61-8, TSK6, SPB11, TSK6,8

15-Mar

Mon

Spring Break

 

 

17-Mar

Wed

Spring Break

 

 

 

22-Mar

Mon

Model implementation

AAEM61-7

24-Mar

Wed

Neural network

AAEM61-5

HW5 (optional, due 3/31)

Stage 1: Project proposal due

29-Mar

Mon

Neural network

AAEM61-5

31-Mar

Wed

Review

AAEM61-8

 

 

5-Apr

Mon

No class

 

 

 

7-Apr

Wed

Midterm II

 

 

Clustering, association analysis, neural network, model implementation

12-Apr

Mon

Introduction to text mining

 

HW6 (optional, Due 4/28)

Stage 2: Project dataset ready

14-Apr

Wed

Principles of text mining

 

19-Apr

Mon

Exploratory analysis of documents,

Exercise 4 (Text mining)

21-Apr

Wed

Text mining for predictive modeling

 

26-Apr

Mon

Conducting a text mining project

 

28-Apr

Wed

Exercise 5

SPB3, RG10

 

Stage 3: Project data exploration and pre-analysis

3-May

Mon

Introduction of Internet marketing

 

 

7-May

Fri

Final Exam (Session 1)

(BA363)

 

 

8:30-10:30a

8-May

Sat

Final Exam (Session 2)

(BA363)

 

 

8:30-10:30a

10-May

Mon

 

 

 

Stage 4: Project report due