近似的归纳推理

Q4 Mathematics 信息与控制 Pub Date : 1986-08-01 DOI:10.1016/S0019-9958(86)80002-X
James S. Royer
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引用次数: 31

摘要

在本文中,我们研究了归纳推理识别准则,它允许在解释中有无限多的错误,但要求这些错误的“密度”不超过一个特定的、预先指定的量。我们引入了这样的准则的三个层次,每个层次都具有与实单位区间相同的阶型。这三个层次在衡量解释错误密度的方式上逐渐变得更加严格。三种标准中最严格的一种,除了一种以外,它的所有条件都与允许在解释中出现有限多错误的鉴定标准无法相比。
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Inductive inference of approximations

In this paper we investigate inductive inference identification criteria which permit infinitely many errors in explanations, but which require that the “density” of these errors be no more than a certain, prespectified amount. We introduce three hierarchies of such criteria, each of which has the same order type as the real unit interval. These three hierarchies are progressively more strict in the way they measure density of errors of explanations. The strictest of the three turns out to have all of its members, save one, incomparable to the identification criterion which permits finitely many errors in explanations.

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来源期刊
信息与控制
信息与控制 Mathematics-Control and Optimization
CiteScore
1.50
自引率
0.00%
发文量
4623
期刊介绍:
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