CS 584: Data Mining

https://www.dropbox.com/request/7OTZCGDp67safc1Yjr34

Dear Presenters for Dec 12,

Please upload your presentations in PDF or PPTX/PPT via the link above by Dec 12, 10 am EST. 

Remember:  Each presentation should be timed to be 10 min + 2 minutes of questions. 

Thanks for all the wonderful presentations last night -- Don't forget to Vote @91

Huzefa

Here is a grading rubric for the presentation: https://cs.gmu.edu/~hrangwal/node/366

and grading rubric for the report: https://cs.gmu.edu/~hrangwal/node/365

Here is a sample suggestion of what should go in a 8-page (max) report:  https://cs.gmu.edu/~hrangwal/files/project.pdf

Here is the allocation for projects. Please let me know if I missed anyone. 

Thanks,

Huzefa

December 5, 2016 (10 projects)

• Sneha Nagpaul
• Veda Gaddam, KALYANI RACHAKONDA, Zain Ibrahim
• Dan Robinson, Benjamin Lafko
• Joseph Carneiro
• Nitya Nair, Devika Ashok, 
• Yujing Chen, H. Zhang
• Yang Zhou
• Li Zhang
• Patcharaporn Munchupaiboon, Voravan Charnsawat
• Ben Brumback
• Rob Jarvis and Jeff Schneider

December 12, 2016 (11 projects)

• Darron Fuller, S. Armstrong, N. Christian
• Niharika Bitra

• Bhavika Tekwani
• TImothy Norton
• Abhishek Kamath
• Kyle Jackson, R. Troung
• Ananya Sain Dhawan
• Adithya Velayudham
• Nathan Obert
• Christian Contreras
• Ting Zhang

Survey Link for Evaluation of Miner: 

https://goo.gl/forms/YueGSMdQ6XDIXiuq2

Dear All,

For CS 584 Data Mining, I designed and developed miner; an analytics competition hosting framework that allowed for submissions of prediction and clustering models for blind evaluation. My goals were to encourage you to learn the class topics by a ``learning-by-doing'' philosophy and implementing your own creative solutions towards each of the four home works.

I want to assess how the this framework and the four home-works helped you learn about data mining and analytics tasks within the context of real world applications.

I would like to hear from you. Positives or Negatives or anything.

Thank you for your time and providing me feedback as I develop and improve this service for future classes.

Huzefa

PS: This is an anonymous survey.

Dear All, 

Good luck for the mid-term exam today.

Huzefa

Dear All, 

Please find attached project proposal requirements that are due on 10/31/2016.

project_proposal_F2016.pdf

Thanks,

Huzefa

Exam on 10/17 will be closed*. Calculators OK. 

Readings from Text Book "Introduction to Data Mining" by Tan et. al.

• Chapters 1, 2, 4, 5 and 8

Sample Exam Questions from Prior Years: 

Data Source: https://archive.ics.uci.edu/ml/datasets/Dorothea

Logs: log.txt

True Labels: dorothea_valid.labels.txt

Huzefa