Computational learning and probabilistic reasoning
This book is devoted to two interrelated techniques for solving some important problems in machine intelligence and pattern recognition, namely probabilistic reasoning and computational learning. Part one describes several new inductive principles and techniques used in computational learning. Part two contains chapters on Causal Probabilistic Modes, model selection, and application of Bayesian networks to multivariate statistical analysis -- The third part is on Bayesian Belief Networks and hybrid systems. The fourth part describes some related theoretical work in the field of probabilistic reasoning
印刷版图书, English, 1996
Wiley / UNICOM, Chichester, 1996