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A Comparison of Two Methods of Inductive Knowledge Acquisition for Medical Knowledge-Based Systems

机译:基于医学知识的系统的两种归纳知识获取方法的比较

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摘要

This paper examines the use of inductive machine learning for knowledge acquisition, and compares two inductive learning programs, CRLS and C4, with respect to their classification accuracy and comprehensibility on the task of generating decision rules by induction from two medical databases. Each program shows the ability to outperform the other in classification accuracy, depending on the database and the nature of the data. Decision trees and criteria tables are compared and contrasted with respect to comprehensibility, and both are seen to have advantages and drawbacks.
机译:本文研究了归纳式机器学习在知识获取中的应用,并比较了两个归纳式学习程序CRLS和C4的分类准确性和可理解性,以从两个医学数据库中归纳生成决策规则。根据数据库和数据的性质,每个程序都显示出在分类精度方面胜过其他程序的能力。对决策树和标准表进行了比较,并就可理解性进行了对比,它们都具有优缺点。

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