2026-09-29T09:04:47Zhttps://skemman.is/oai/request

oai:skemman.is:1946/349152020-01-21T11:13:34Zcom_1946_6870com_1946_6001col_1946_34325

Háskólinn í Reykjavík Kristófer Reynisson 1995- Yngvi Björnsson 1964- Payment card fraud poses a problem with widespread implications. However, the class imbalance between genuine and fraudulent transactions presents a challenge to traditional learning methods. Cost-based methods address this problem by assigning different costs to the misclassification of each class. Sahin et al. [7] define a cost-sensitive decision tree algorithm, and this study attempts to both replicate and build on their findings. The results presented here do not support the hypothesis that the cost-sensitive algorithm provides an improvement over traditional decision tree algorithms. However, the results do suggest that different methods of prioritizing alerted transactions can lead to performance improvements over some measures. 2020-01-21T11:13:34Z 2020-01-21T11:13:34Z 2020-01-21T11:13:34Z 2019-12-13T14:02:27Z 2019-12 http://hdl.handle.net/1946/34915 en Tölvunarfræði Greiðslukort Afbrot Gervigreind Computer science Credit cards Crime Artificial intelligence A replication of a cost-sensitive decision tree approach for fraud detection Thesis Bachelor's