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COMPLEXITY-DRIVEN EVOLUTION OF META-AGENTS FOR CLASSIFICATION OF MEDICAL DATA

机译:复杂性驱动的用于医学数据分类的元代理进化

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We study the possibility of constructing decision graphs with the help of several agents. We present a two-leveled evolutionary algorithm for the induction of decision graphs and describe the principle of classification based on the decision graphs. Several agents are used to construct the decision graphs. They are constructed and evolved with the help of automatic programming and evaluated with a universal complexity measure. The developed model is used for the classification of patients with mitral valve prolapse syndrome.
机译:我们研究了在几个代理的帮助下构造决策图的可能性。我们提出了用于决策图归纳的两级进化算法,并描述了基于决策图的分类原理。使用多个代理来构建决策图。它们在自动编程的帮助下构建和发展,并通过通用的复杂性度量进行评估。所开发的模型用于对二尖瓣脱垂综合征的患者进行分类。

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