Todd B S
St Cross College, Oxford, U.K.
Int J Biomed Comput. 1990 Jul;26(1-2):29-38. doi: 10.1016/0020-7101(90)90017-o.
When diagnostic programs are constructed within a probabilistic framework, it is often the case that computation of joint probabilities of exhaustive combinations of events is easy, but computation of the kind of conditional probabilities the user wishes to know, is hard. This paper describes a simple algorithm for computing the required values, and then suggests several heuristic optimizations that may enable suitable approximations to be obtained in a feasible time when the task is otherwise intractable. An account is given of a specific application of the method in the construction of a medical diagnostic program, which is described in more detail elsewhere.
当在概率框架内构建诊断程序时，通常会出现这样的情况：计算事件详尽组合的联合概率很容易，但计算用户想要知道的那种条件概率却很困难。本文描述了一种用于计算所需值的简单算法，然后提出了几种启发式优化方法，当任务在其他情况下难以处理时，这些方法可能能够在可行的时间内获得合适的近似值。文中介绍了该方法在构建医学诊断程序中的一个具体应用，该应用在其他地方有更详细的描述。
