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Semi-Supervised Learning with Graph Transduction. Prof: Latecki Evaluators: Nancy & Nouf. 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
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Semi-Supervised Learning with Graph Transduction Prof: Latecki Evaluators: Nancy & Nouf
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
Average Classification Accuracy= 85.49% • Maximum Accuracy = 87.44% • Average Time = 0.4877 • Didn’t work on Shuffled datasets Alpha Team
Average Classification Accuracy= 91.31% • Maximum Accuracy = 92.48% • Average Time = 8.7347 • Accuracy of Shuffled Dataset = 88.66% Beta Team
Average Classification Accuracy= 84.17% • Maximum Accuracy = 86.92% • Average Time = 20.1597 • Accuracy of Shuffled Dataset = 84.17% Gamma Team
Average Classification Accuracy= 89.26% • Maximum Accuracy = 90.45% • Average Time = 0.5199 • Didn’t work on Shuffled datasets Delta Team
Average Classification Accuracy = 86.92% • Maximum Accuracy = 88.05 • Average Time = 4.9691 • Accuracy of Shuffled Dataset = 86.92 % Epsilon Team
Average Classification Accuracy = 85.32% • Maximum Accuracy = 87.52 • Average Time = 0.1515 • Didn’t work on Shuffled datasets Zeta Team
The highest average accuracy is 91.31% • The winner is : Beta team!! Winner Team
Alpha: Bernardo F. Juncal, An Dang, Feipeng Zhao • Beta: Chi Zhang, Kier Heilman, Cao Yuan • Gamma: AnjanNepal, Peiyi Li, Liya Ma • Delta: Howard Liu, Motaz Al-Hami, SemirElezovikj • Epsilon : David Dobor, LakeshKansakar, Tiffany Nguyen • Zeta: Jesse Glass, Joseph Catrambone, Jeff Newell Participated Teams