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GA-CatBoost-Weight Algorithm for Predicting Casualties in Terrorist Attacks: Addressing Data Imbalance and Enhancing Performance

Terrorism poses a significant threat to international peace and stability. The ability to predict potential casualties resulting from terrorist attacks, based on specific attack characteristics, is vital for protecting the safety of innocent civilians. However, conventional data sampling methods str...

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Uloženo v:
Hlavní autoři: Yuxiang He, Baisong Yang, Chiawei Chu
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI AG 2024-03-01
Edice:Mathematics
Témata:
terrorist attack prediction
feature selection
CatBoost
sample imbalance
On-line přístup:https://www.mdpi.com/2227-7390/12/6/818
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