Fusing xgboost and shap models for maritime accident prediction and causality interpretability analysis

HIGHLIGHTS

  • who: Cheng Zhang and collaborators from the School of Law, Fuzhou University, Fuzhou, China have published the article: Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis, in the Journal: (JOURNAL)
  • what: The study discussed the consequences of collisions caused by different types of human error and tried to solve the small sample problem in conditional probability table estimation, especially to fully examine the influence of external factors on human errors in the case of insufficient collision records. This study applied a random forest algorithm (RF) and a logistic regression algorithm . . .

     

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