01456nam a2200205Ia 4500 CTU_153169 210402s9999 xx 000 0 und d 70.73 519.5 B357 Bayesian networks : A practical guide to applications Edited by Olivier Pourret , Patrick Naim, Bruce Marcot Hoboken, NJ John Wiley c2008 Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. Bayesian statistical decision theory,Mathematical models,Lý thuyết thống kê Bayesian,Mô hình toán học QHieu Trung tâm Học liệu Trường Đại học Cần Thơ