Feature generation and contribution comparison for electronic fraud detection

HIGHLIGHTS

• who: Yen-Wu Ti from the suspicious activities created based on past observations or suggestions from police agenciesHowever, a TaiwanYango University have published the research work: Feature generation and contribution comparison for electronic fraud detection, in the Journal: Scientific Reports Scientific Reports of 10/Oct/2022
• what: The features the authors propose meet the needs of banks. The authors do not use public datasets in the experiments , as the limited nature of the information provided in such datasets makes them unsuitable for verifying the proposed model. There is a trade-off between these two rates . . .
  

   

  

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