1. Semi-Supervised Learning with Graph Transduction
Prof: Latecki
Evaluators: Nancy & Nouf

2. Dataset WE generated two different GROUPS of dataset for testing:
5 different datasets from the original data
Calculated mean accuracy and time
These were used for the evaluation
For further testing, we shuffled the data and repeated the testing
These results will not be taken into account for the decision of the winning team
Dataset

3. Alpha Team Average Classification Accuracy= 85.49%
Maximum Accuracy = 87.44%
Average Time =
Didn’t work on Shuffled datasets
Alpha Team

4. Beta Team Average Classification Accuracy= 91.31%
Maximum Accuracy = 92.48%
Average Time =
Accuracy of Shuffled Dataset = 88.66%
Beta Team

5. Gamma Team Average Classification Accuracy= 84.17%
Maximum Accuracy = 86.92%
Average Time =
Accuracy of Shuffled Dataset = 84.17%
Gamma Team

6. Delta Team Average Classification Accuracy= 89.26%
Maximum Accuracy = 90.45%
Average Time =
Didn’t work on Shuffled datasets
Delta Team

7. Epsilon Team Average Classification Accuracy = 86.92%
Maximum Accuracy = 88.05
Average Time =
Accuracy of Shuffled Dataset = %
Epsilon Team

8. Zeta Team Average Classification Accuracy = 85.32%
Maximum Accuracy = 87.52
Average Time =
Didn’t work on Shuffled datasets
Zeta Team

9. Winner Team The highest average accuracy is 91.31%
The winner is : Beta team!!
Winner Team

10. Participated Teams Alpha: Bernardo F. Juncal, An Dang, Feipeng Zhao
Beta:      
Chi Zhang, Kier Heilman, Cao Yuan
Gamma:      
Anjan Nepal, Peiyi Li, Liya Ma
Delta:     
Howard Liu, Motaz Al-Hami, Semir Elezovikj
Epsilon :      
David Dobor, Lakesh Kansakar, Tiffany Nguyen
Zeta:      
Jesse Glass, Joseph Catrambone, Jeff Newell
Participated Teams