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

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

Alpha Team Average Classification Accuracy= 85.49% Maximum Accuracy = 87.44% Average Time = 0.4877 Didn’t work on Shuffled datasets Alpha Team

Beta Team Average Classification Accuracy= 91.31% Maximum Accuracy = 92.48% Average Time = 8.7347 Accuracy of Shuffled Dataset = 88.66% Beta Team

Gamma Team Average Classification Accuracy= 84.17% Maximum Accuracy = 86.92% Average Time = 20.1597 Accuracy of Shuffled Dataset = 84.17% Gamma Team

Delta Team Average Classification Accuracy= 89.26% Maximum Accuracy = 90.45% Average Time = 0.5199 Didn’t work on Shuffled datasets Delta Team

Epsilon Team Average Classification Accuracy = 86.92% Maximum Accuracy = 88.05 Average Time = 4.9691 Accuracy of Shuffled Dataset = 86.92 % Epsilon Team

Zeta Team Average Classification Accuracy = 85.32% Maximum Accuracy = 87.52 Average Time = 0.1515 Didn’t work on Shuffled datasets Zeta Team

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

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