CSCE 822 Home Page Syllabus Homework/Projects Powerpoint Slides

CSCE 822 Data Mining and Warehousing

Announcements

Homework assignment 5 can be found on the HomeWork/Projects page.
Project Presentations begin on Tuesday November 26th

Class Meeting Times

Section Days Time Room
Lecture 001 T, Th 10:05am - 11:20am Swearingen 2A11

Instructor

Prof. John Rose
Office:Swearingen 3A67
E-mail:rose@cse.sc.edu
Office Phone:777-2405
Office Hours:TTh 3:30pm-5pm and by appointment

Text

  • Introduction to Data Mining by Tan, Steinbach, and Kumar, Addison Wesley, 2005.

  • Alternative Text: Data Mining: Concepts and Techniques (3rd Edition) by Jiawei Han and Micheline Kamber, Morgan Kaufmann, 2011.

  • Possibly also readings will come from the big data/data mining/data analytics literature.

    Prerequisites

    Ability to think

    Grade breakdown

    Homework40%
    Project: Preproposal, Proposal, Presentation and Final Report40%
    Midterm Exam20%

    Grade ranges

    A90 - 100B+86 - 89B80 - 85
    C+76 - 79C70 - 75D+66 - 69
    D60-65Fbelow 60
    Grades will not be curved. You will receive the grade that you have earned. N.B. If you want to receive a passing grade, then you must earn it during the semester.

    Resources you may find useful

    R download for Linux, Mac OS, and Windows
    R Studio download for linux, Mac OS, and Windows
    Weka:Data Mining Software in Java download
    libsvm with Weka download
    mloss: unsundry open source machine learning software website

    Computer Science and Engineering University of South Carolina

    If you have any questions or comments, please send me e-mail at: rose@cse.sc.edu

    CSCE 822 Home Page Syllabus Homework/Projects Powerpoint Slides