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Pattern Classification with Imbalanced and Multiclass Data for the Prediction of Albendazole Adverse Event Outcomes
2016
Procedia Computer Science
Class imbalance problem is one of the important problems for classification studies in data mining. In this study, a comparative analysis of some sampling methods was performed based on the evaluation of four classification algorithms for the prediction of albendazole adverse events outcomes. Albendazole is one of the main medications used for the treatment of a variety of parasitic worm infestations. The dataset was created from the public release of the FDA's FAERS database. Four sampling
doi:10.1016/j.procs.2016.04.216
fatcat:ptqt5jd7nrbh3j7r3v353xurte