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ILLM——作为一种预测预期寿命实现情况的方法的归纳学习算法。

ILLM--inductive learning algorithm as a method for prediction of life expectancy achieving.

作者信息

Kern J, Gamberger D, Sonicki Z, Vuletić S

机构信息

University of Zagreb, Medical School, Andrija Stampar School of Public Health, Croatia.

出版信息

Stud Health Technol Inform. 1997;43 Pt B:656-60.

Abstract

The aim of the paper was to use inductive learning algorithm ILLM in the field of epidemiology, for prediction the life expectancy achieving. Data base comprised results of epidemiological investigation in some regions of Croatia. Overall accuracies for different samples and corresponding rules produced by ILLM algorithm, showed some interesting results. Algorithm can be seen as having the capacity to forecast 'achieving the life expectancy'. In the same time algorithm was not able to make a good forecast for 'not achieving the life expectancy'.

摘要

本文的目的是在流行病学领域使用归纳学习算法ILLM,以预测预期寿命的实现情况。数据库包含克罗地亚某些地区的流行病学调查结果。ILLM算法针对不同样本产生的总体准确率及相应规则显示出一些有趣的结果。该算法可以被视为具有预测“实现预期寿命”的能力。同时,该算法无法对“未实现预期寿命”做出良好预测。

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