CS 57300: Data Mining

TR 10:30-11:45

GRIS 103

Chris Clifton

Email: clifton_nospam@cs_nojunk.purdue.edu

Course Outline

Course Topics

Data Mining has emerged at the confluence of artificial intelligence, statistics, and databases as a technique for automatically discovering summary knowledge in large datasets. This course introduces students to the process and main techniques in data mining, including classification, clustering, and pattern mining approaches. Data mining systems and applications are also covered, along with selected topics in current research.

Prerequisites

STAT516 or an equivalent introductory statistics course, CS 381 or an equivalent course on computing theory, and coursework that covers a reasonable level of programming skills (e.g., a CS major or minor, or STAT 598G). If you feel you may not have sufficient background, please contact the instructor.

IF YOU HAVE BEEN UNABLE TO REGISTER FOR THE COURSE

This course is anticipated to be oversubscribed, and as such registration is initially limited to CS students. If you have been unable to register, please follow the CS department process for waitlisting/registration. Please do not ask the instructor for an override, I have been told that if the course is shown as full, the registrar will not allow registration even with a form 23 signed by the instructor. Please follow the process above or consult with your advisor.

Teaching Assistants

Instructor Office Hours

Thursday 2:15-4pm, HAAS 222.

Also by appointment. Email a few good times for you and I'll pick what works. (This also works for setting up a videoconference.) You can just drop by, I'm often in, and if not tied up with something that has be be finished right away I'll be happy to meet with you.

Mailing List

There will be a course email list used for high-priority announcements. This will use your @purdue.edu email address; make sure this is forwarded to someplace you look on a regular basis.

We will be using Gradescope to turn in and comment on assignments; Brightspace will be used for recording and distributing grades, as well as for any other non-public information about the course.

Course Methodology

The course will primarily be taught through lectures, supplemented with reading.

The primary reading will be from the text. The written assignments and projects are also a significant component of the learning experience.

For review (and if you miss a lecture), you can pick them up as an Boilercast vodcast/podcast (accessible through Brightspace)

We will be using Campuswire to facilitate discussions; this will enable you to post questions as well as respond to questions posted by others. Be aware that the default is for posts to be identified and visible to everyone. You are also encouraged to hold discussions with other students, via videoconference if you wish. Purdue has paid licenses for WebEx and Zoom. Please keep the collaboration guidelines below in mind, just as if you were meeting in person.

Evaluation/Grading

Evaluation is a somewhat subjective process (see my grading standards), however it will be based on your understanding of the material as evidenced in:

Late work will be penalized 15% per day (24 hour period or fraction thereof). The penalty is based on possible points, not your actual score (so after 5 days, if your submission garners less than 75% of the possible points, you get a 0.) Each assignment has a hard deadline of five days after the published due date, after which the solution sets go out and no further submissions are accepted. Also note that the last day of class will be a hard deadline for all work. You are allowed five--> five extension days, to be used at your discretion throughout the semester (illness, job interviews, etc.); no penalty is assessed for late work within this limit. If your assignments add up to more than five days late over the semester, the late days will be automatically applied to the highest value assignments (e.g., projects), so the 15% late penalties are applied to the lower value assignments first. Late penalties will only be applied at the end of the semester, so if you go beyond the alotted late days, you may see your score for some assignments drop. You must keep track of late days yourself. Fractional use is not allowed, and this may not be used to extend submission past the hard deadline (five days after the deadline, or last day of class, whichever comes first.)

Policy on Intellectual Honesty

Please read the departmental academic integrity policy above. This will be followed unless I provide written documentation of exceptions. You should also be familiar with the Purdue University Code of Honor and Academic Integrity Guide for Students. You may also find Professor Spafford's course policy useful - while I do not apply it verbatim, it contains detail and some good examples that may help to clarify the policies above and those mentioned below.

In particular, I encourage interaction: you should feel free to discuss the course with other students. However, unless otherwise noted work turned in should reflect your own efforts and knowledge.

For example, if you are discussing an assignment with another student, and you feel you know the material better than the other student, think of yourself as a teacher. Your goal is to make sure that after your discussion, the student is capable of doing similar work independently; their turned-in assignment should reflect this capability. If you need to work through details, try to work on a related, but different, problem.

If you feel you may have overstepped these bounds, or are not sure, please come talk to me and/or note on what you turn in that it represents collaborative effort (the same holds for information obtained from other sources that provided substantial portions of the solution.) If I feel you have gone beyond acceptable limits, I will let you know, and if necessary we will find an alternative way of ensuring you know the material. Help you receive in such a borderline case, if cited and not part of a pattern of egregious behavior, is not in my opinion academic dishonesty, and will at most result in a requirement that you demonstrate your knowledge in some alternate manner.

Other Issues and Resources

If you have other issues please feel free to talk to me - if I can't help, I'll try to point you in the right direction. Be aware that due to Title IX and state law, there are some things for which I can't promise confidentiality (but see CARE below).

University Emergency Preparedness instructions. Note: In the event of weather-related class cancellation, we will probably transition to live online (which would be recorded, as with Boilercast), which you should all be familiar with. If there is a weather-related cancellation, watch your email.

Nondiscrimination Statement: Purdue University is committed to maintaining a community which recognizes and values the inherent worth and dignity of every person; fosters tolerance, sensitivity, understanding, and mutual respect among its members; and encourages each individual to strive to reach his or her own potential. In pursuit of its goal of academic excellence, the University seeks to develop and nurture diversity. The University believes that diversity among its many members strengthens the institution, stimulates creativity, promotes the exchange of ideas, and enriches campus life. Purdue’s nondiscrimination policy can be found at http://www.purdue.edu/purdue/ea_eou_statement.html.

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, you are welcome to let me know so that we can discuss options. You are also encouraged to contact the Disability Resource Center at: drc@purdue.edu or by phone: 765-494-1247.

Student Mental Health and Wellbeing: Purdue University is committed to advancing the mental health and wellbeing of its students. If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at (765)494-6995 and http://www.purdue.edu/caps/ during and after hours, on weekends and holidays, or through its counselors physically located in the Purdue University Student Health Center (PUSH) and the Psychology building (PSYC) during business hours.

Sexual Violence: Purdue University is devoted to fostering a secure, equitable, and inclusive community. If you or someone you know has been the victim of sexual violence and are interested in seeking help, there are services available. Reporting the incident to any Purdue faculty and certain other employees, including resident assistants, will lead to reference to the Title IX Coordinator, as these individuals are mandatory reporters. The Title IX office can investigate report of sex-based discrimination, sexual harassment, or sexual violence. Title IX ensures that both parties in a reported event have equal opportunity to be heard and participate in a grievance process. To file an online report visit https://cm.maxient.com/reportingform.php?PurdueUniv&layout_id=15 or contact the Title IX coordinator at 765-494-7255.

The Center for Advocacy, Response, and Education (CARE) offers confidential support and advocacy that does not require the filing of a report to the Title IX office. The CARE staff helps each survivor assess their reporting options and access resources that meet personal needs. The CARE office can be found at 205 North Russell Street in Duhme Hall (Windsor), room 143 Monday - Friday 8:00 AM to 5:00 PM. They can also be reached at their 24/7 hotline 765-495-CARE or at CARE@purdue.edu.

And you should always feel free to call, email, or drop by and talk to me (or, if you have an issue with me, to the department head.)

Text

The basic text for this course is:

Principles of Data Mining
D. Hand, H. Mannila, P. Smyth
MIT Press, ISBN ISBN 9780262304085 , 2001.

Course Outline (numbers correspond to week):

  1. Assignment 1 released, due 1/21.
  2. Assignment 2 released, due 2/14.
  3. Project proposal due 2/21 11:59pmEST
  4. Drop date: March 11
    Spring Vacation: March 14-18
  5. Descriptive Modeling
  6. Project Part 2 due 3/28 11:59pmEDT
  7. Pattern Mining
  8. Ethics Issues:
  9. Project writeup due 4/25 11:59pmEDT
    Final project 10 minute lightning talks this week.

Final Exam Monday, May 2, 7:00pm-9:00pm EDT in GRIS 103.
If you have another exam scheduled at that time or you have three or more exams scheduled the same day and would like to reschedule this exam, please let me know as soon as possible. Note that conflicting exams are pretty much the only reason for rescheduling, I bought a ticket to go home earlier is not an accepted reason for an exam to be rescheduled.


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