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Lựa chọn biến Bayesian thưa trong mô hình probit hạt nhân để phân tích dữ liệu có chiều cao
Tóm tắt
Trong bài báo này, chúng tôi phát triển một phương pháp lựa chọn biến Bayesian thưa trong mô hình probit hạt nhân cho phân loại dữ liệu có chiều cao. Đặc biệt, chúng tôi thiết lập một phân phối prior tương quan trên kích thước mô hình và một phân phối prior thưa trên các tham số hồi quy. Các thuật toán tính toán dựa trên MCMC được phác thảo để tạo ra các mẫu từ các phân phối hậu nghiệm. Các nghiên cứu mô phỏng và dữ liệu thực tế cho thấy rằng, về độ chính xác của việc lựa chọn biến và phân loại, phương pháp chúng tôi đề xuất hoạt động tốt hơn so với năm phương pháp Bayesian khác không có tham số tương quan trong prior hoặc những phương pháp chỉ liên quan đến một tham số thu nhỏ.
Từ khóa
#Lựa chọn biến #Bayesian #thưa #mô hình probit #hạt nhân #phân loại dữ liệu chiều cao.Tài liệu tham khảo
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