Research on the Predictive Models for Abnormal Behavior of Drug Violation Based on Ensemble Learning
Through machine learning and deep learning,hidden relationships in drug violation abnormal behavior data could be extracted in the complex and dynamic environment,which had broad application prospects in the field of predictive policing and crime combating.However,the traditional machine learn-ing algorithm could not achieve good prediction effect in"combating drug crime and preventing drug crime".Therefore,a fusion model based on k-fold bagging ensemble learning was proposed.Firstly,ma-chine learning and deep learning models were optimized as the base learner.Then,k-fold bagging meth-od was selected for ensemble training.Finally,hard voting strategy was adopted to obtain the model with the best predictive performance.The results showed that the accuracy of the ensemble learning model on the two training sets was 9.82％and 6.96％higher than the average accuracy of the single base model.Meanwhile,the model had been successfully applied to the prediction of abnormal behavior of drug viola-tion,indicating a new direction for the deep application of ensemble learning in the prediction of police and crime combating.
abnormal behavior of drug violationpredictive policingensemble learningpredictive modelscombating criminals
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