So sánh giữa hồi quy logistic, cây phân loại và hồi quy, và mô hình mạng nơ-ron trong dự đoán tái phạm bạo lực

Journal of Quantitative Criminology - Tập 27 - Trang 547-573 - 2011
Yuan Y. Liu1, Min Yang1,2, Malcolm Ramsay3, Xiao S. Li1, Jeremy W. Coid4
1Department of Health Statistics, School of Public Health, Sichuan University, Chengdu, China
2Division of Psychiatry, School for Community Health Sciences, University of Nottingham, Nottingham, UK
3Partnerships and Health Strategy Unit, Ministry of Justice, London, UK
4Forensic Psychiatry Research Unit, Queen Mary University of London, London, UK

Tóm tắt

Các nghiên cứu trước đây đã so sánh hồi quy logistic (LR), cây phân loại và hồi quy (CART), và mô hình mạng nơ-ron (NNs) về tính hợp lệ dự đoán và cho thấy kết quả không đồng nhất trong việc chứng minh sự ưu việt của bất kỳ mô hình nào. Ba mô hình đã được thử nghiệm trên một mẫu dự prospect gồm 1225 tù nhân nam ở Vương quốc Anh, được theo dõi trung bình 3,31 năm sau khi ra tù. Các chỉ số trong một công cụ đánh giá rủi ro được sử dụng rộng rãi (Hồi ức, Lâm sàng, Quản lý rủi ro -20, hoặc HCR-20) đã được sử dụng làm biến dự đoán và tái phạm bạo lực làm biến đầu ra. Quy trình đa xác thực đã được sử dụng để giảm thiểu sai số mẫu trong việc báo cáo độ chính xác dự đoán. Tỷ lệ cơ bản thấp đã được kiểm soát bằng cách sử dụng các biện pháp khác nhau trong ba mô hình để giảm thiểu lỗi dự đoán và đạt được phân loại cân bằng hơn. Độ chính xác tổng thể của ba mô hình dao động từ 0,59 đến 0,67, với phạm vi AUC tổng thể từ 0,65 đến 0,72. Mặc dù hiệu suất của NNs tốt hơn một chút so với các mô hình LR và CART, nhưng nó không cho thấy sự cải thiện đáng kể.

Từ khóa

#hồi quy logistic #cây phân loại và hồi quy #mô hình mạng nơ-ron #tái phạm bạo lực #độ chính xác dự đoán

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