1. Data Mining and Electronic Business: Technology, Information, and Innovation Class 2 Stat252 Summer 2004 Stanford University Andreas S. Weigend, Ph.D. Chief Scientist, BV Capital Founder, Weigend Associates LLC Dates T 6/29 W 6/30  T 7/6 W 7/7 M 7/12 (+ party) T 7/13 M 7/19 T 7/20 M 7/26 T 7/27 W 7/28 T 8/3 Time: 3:15pm - 5:00pm

2. 2 © 2004 by Weigend Associates LLC | www.weigend.com Agenda Class 2 Summary of Class 1 Discussion: What were the main insights obtained in Class 1? Organization TAs Project Textbooks  Background reading  Technology: BFS Ch2  Statistics: B&L Ch5 Lecture Introduction to e-Business

3. 3 © 2004 by Weigend Associates LLC | www.weigend.com Logistics Andreas S. Weigend. Ph.D. Contact during class via Yahoo messenger: andreasweigend@yahoo.com General information at www.weigend.com Teaching Assistants TA for students coming to class  Armin Schwartzman  Office hours: Mon and Tue 2:15 – 3:00. Sequoia 238, or by appointment armins@stanford.edu TA for students taking course remotely, and students who prefer communicating through email  Eric Bair  ebair@stanford.edu TA responsibilities Help with:  Data analysis and statistics background, technical questions  Questions about assigned readings  Logistics

4. 4 © 2004 by Weigend Associates LLC | www.weigend.com Project Define a data mining problem in e-Business What are the objectives? What (management) decisions will this project support? What data do you need to collect?  Be specific, discuss difficulties, order of magnitude etc. What initial analysis will you perform? What data mining algorithms will you apply, and why? What resources do you expect it to take?  Timeline, budget… Evaluation criteria Relevance of problem Crispness of the proposal Originality, creativity Suitability of analysis techniques  Definition of appropriate baselines for comparison

5. 5 © 2004 by Weigend Associates LLC | www.weigend.com Project Logistics Group size: 2-3 students Remote students, if you need partner, please contact TA Timeline  Submit by email to your TA by end of the day (all deadlines are Sunday evening) Jul 11: One-pager  Key idea  Feedback to students by Jul 14 Jul 25: Proposal as text document Aug 1: Presentation  8 – 12 slides Bonus The best 2-3 project proposals will be presented in the Aug 3 class  The winners will announced at the beginning of that class Encouragement Contact me if you are interested in discussing it with some of the data-intensive companies who had sent their data mining heads to the first class