Urban crime trends analysis and occurrence possibility prediction based on light gradient boosting machine
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AbstractBig Data and Machine learning have been increasingly used to fight against Urban crimes. Our goal is to discover the connection between crime-related factors and the underlying complex crime pattern. Therefore, to predict the possibility of crime occurrence. Light Gradient Boosting Machine (LightGBM) Model is adopted in our study to predict the crime occurrence possibility based on actual crime information. We found that the prediction results are approximately consistent with an actual variation. We hope this work could help with crime prevention and policing.
CitationTong X, Ni P, Li Q, Yuan Q, Liu J, Lu H, Li G (2021) 'Urban crime trends analysis and occurrence possibility prediction based on light gradient boosting machine', 2021 IEEE 4th International Conference on Big Data and Artificial Intelligence (BDAI) - Qingdao, Institute of Electrical and Electronics Engineers Inc..
TypeConference papers, meetings and proceedings
SponsorsThis study is partially supported by the AI University Research Centre (AI-URC) through the XJTLU Key Program Special Fund (KSF-P-02) and KSF-A-17
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