Based on the data of Siberian tigers taken by infrared cameras in Hunchun from 2014 to 2019,a risk classification model of tiger infested areas was constructed using XGBoost algorithm.The model test showed that the accuracy rate of the model was 93.51％,the precision was 93.85％,the recall rate was 93.08％,the F1-score value was 93.31％,and the Cohen's Kappa statistical coefficient was 90.2％.The research results showed that the risk classification model of human-tiger coexistence area based on XGBoost algorithm had good classification effect and high prediction accuracy.It was feasible to use this model to classify the risk level of human-tiger coexistence area.
关键词
人-虎共存区域/XGBoost算法/风险等级/划分模型/红外相机陷阱
Key words
human-tiger coexistence area/XGBoost algorithm/risk level/model division/infrared camera traps
万方数据