Monday, Wednesday 4:15-5:30 PM in Huang Engineering Center 18 Professor Rajan Patel Email: stats202 [at] gmail [dot] com Phone: 813.810.6915 (leave a message and I will return your call as soon as I can) Office: Sequoia Hall (specific room TBD) Office Hours: Monday 5:30PM-7:00 PM and by appointment TA Information: TBD Course Web Page: http://sites.google.com/site/stats202
Course Description: Data mining is used 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: decision trees, neural networks, association rules, clustering, case based methods, and data visualization. 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 (naive bayes models, support vector machines) Chapter 8 - Cluster Analysis: Basic Concepts and Algorithms Chapter 10 - Anomaly Detection Evaluation: Grades will be based on 3 components: 4 homework assignments (worth 40 points each), a single midterm exam (worth 100 points) and a comprehensive in-class final exam (worth 200 points). The midterm exam date will be Wednesday, July 18. Special arrangements will be made for remote SCPD students who are not able to come to campus for the midterm or the final. There will be an optional class project (worth 200 points) which can replace the point total of the final exam. If you choose to take the in-class final and submit the class project, we will use the maximum score of the two as your score for the final. Grades: Grades will be assigned as follows: 98%-100% = A+ 93%-98% = A 90%-93% = A- 85%-90% = B+ 80%-85% = B 75%-80% = B- 70%-75% = C+ 67%-70% = C 60%-67% = D 50%-60% = F Current point totals will be posted throughout the semester on the course web page. Late Assignments/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 cell phone voice mail or sent by email prior to the start of the exam. An exam must be made up within one week of the original exam date. There will be no exceptions. Late homework assignments will have 5 points deducted for every day they are late. Technology: A basic hand held calculator which has logarithm functionality will be sufficient for the midterm and the final. To complete homework assignments you will need internet access, Microsoft Excel, and the R statistical software package (free download). Academic Honesty: It is essential that you abide by the academic honesty policies of the university. In particular, you may not copy other students' work on exams or homework. |
