Data Mining (BUS 297D) Greensheet, Fall 2009

Professor David Mease

Email: mease_d@cob.sjsu.edu (Email is the preferred contact method)

Phone: Cell = 419-944-9652, Office = 408-924-3523

Office: BT 551

Office Hours: Tuesday = 7:15 AM to 9:15 AM, Thursday = 7:15 AM to 9:15 AM, Friday = 8:15 AM to 9:15 AM and by appointment

Course Web Page: http://www.cob.sjsu.edu/mease_d/bus297D

Textbook: Tan, Steinbach, Kumar, Introduction to Data Mining



Course Description: Data mining is used in industry to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: data visualization, association rules, clustering, and various modern classification techniques including support vector machines, nearest neighbor methods, Random Forests, bagging and boosting.

The following chapters from the textbook will be covered in this order:

Chapter 1 - Introduction
Chapter 2 - Data
Chapter 3 - Exploring Data
Chapter 6 - Association Analysis: Basic Concepts and Algorithms

Chapter 4 - Classification: Basic Concepts, Decision Trees, and Model Evaluation
Chapter 5 - Classification: Alternative Techniques
Chapter 8 - Cluster Analysis: Basic Concepts and Algorithms
Chapter 10 - Anomaly Detection


Course Outline and Schedule:

8/27 (Thursday) - Lecture 1 - Class meeting (6PM to 10PM)

8/29 (Saturday) - Lecture 2 - Online video will be posted on webpage

9/3 (Thursday) - Lecture 3 - Online video will be posted on webpage

9/10 (Thursday) - Lecture 4 - Class meeting (6PM to 10PM) - HW 1 due (70 points)

9/17 (Thursday) - Midterm exam (6PM to 10PM, 100 points) - HW 2 due (30 points)

9/19 (Saturday) - Lecture 5 - Online video will be posted on webpage

9/24 (Thursday) - Lecture 6 - Online video will be posted on webpage

10/1 (Thursday) - Lecture 7 - Class meeting (6PM to 10PM) - HW 3 due (50 points)

10/8 (Thursday) - Lecture 8 - Online video will be posted on webpage

10/15 (Thursday) - Final exam (6PM to 10PM, 100 points) - HW 4 due (50 points)

This is a hybrid course, meaning 1/2 of it is online. We will only have 5 physical meetings: 8/27, 9/10, 9/17, 10/1 and 10/15. These will all be 6PM to 10PM. There will be homework assignments due on the last 4 of these 5 meetings. On 2 of these 5 meetings we will also have exams (following a review).

The other 5 lectures will be online meaning that we will not meet. The videos for these lectures will be posted (by midnight at the latest) on the date listed. You will be responsible for watching these videos before the next class meeting. You should watch them sooner rather than later to have ample time to complete the homework assigned and prepare for the exams.


Prerequisite: Bus 90 (Business Statistics)


Evaluation: Grades will be based on 2 exams worth 100 points each, and 4 homework assignments worth 200 points total as listed above.


Grades: Grades will be assigned as follows:

97%-100% = A+
92%-97% = A
90%-92% = A-
87%-90% = B+
82%-87% = B
80%-82% = B-
77%-80% = C+
70%-77% = C
60%-70% = D
below 60% = F

Current point totals will be posted throughout the semester on the course web page by the last 5 digits of student ID numbers.


Homework: Four homeworks will be assigned and will be due on the dates listed above. These must be printed out using a computer and turned in during the class meeting time. Anything handwritten on the homework will not be counted. Late homeworks will not be accepted.


Make Up Exams: I must receive prior notification and justification of your impending absence in order to authorize a make-up exam. Messages must be left either on my office or cell phone voice mail or sent by email prior to the start of the exam. An exam must be made up within 1 day of the original exam date. There will be no exceptions.


Technology: A basic hand held calculator which can take logarithms in addition to performing standard operations will be sufficient for the midterm exam and the final. To complete homework assignments you will need internet access, Microsoft Excel (2002), the R statistical software package (free download) and a printer.


College of Business Mission:
The College of Business is the institution of opportunity, providing innovative business education and applied research for the Silicon Valley region.


College of Business Policies and Procedures:
To ensure that every student, current and future, has the opportunity to experience an environment that is safe, attractive, and otherwise conducive to learning, the College of Business at San José State has established the following policies:

Eating: Eating and drinking (except water) are prohibited. Students with food will be asked to leave the building. Students who disrupt the course by eating and do not leave the building will be referred to the Judicial Affairs Officer of the University.

Cell Phones: Students will turn their cell phones off or put them on vibrate mode while in class. They will not answer their phones in class. Students whose phones disrupt the course and do not stop when requested by the instructor will be referred to the Judicial Affairs Officer of the University.

Computer Use: In the classroom, faculty allow students to use computers only for class-related activities. These include activities such as taking notes on the lecture underway, following the lecture on Web-based PowerPoint slides that the instructor has posted, and finding Web sites to which the instructor directs students at the time of the lecture. Students who use their computers for other activities or who abuse the equipment in any way, at a minimum, will be asked to leave the class and will lose participation points for the day, and, at a maximum, will be referred to the Judicial Affairs Officer of the University for disrupting the course. (Such referral can lead to suspension from the University.) Students are urged to report to their instructors computer use that they regard as inappropriate (i.e., used for activities that are not class related).

Academic Honesty: Faculty will make every reasonable effort to foster honest academic conduct in their courses. They will secure examinations and their answers so that students cannot have prior access to them and proctor examinations to prevent students from copying or exchanging information. They will be on the alert for plagiarism. Students who are caught cheating will be reported to the Judicial Affairs Officer of the University, as prescribed by Academic Senate Policy F06-1.

I will follow the protocol described at http://sa.sjsu.edu/judicial_affairs/faculty_and_staff/academic_integrity/reporting.html when dealing with any violations.