基于遗传算法和案例推理的自动诊断

J.M. Garrell i Guiu, E. Golobardes i Ribé, E. Bernadó i Mansilla, X. Llorà i Fàbrega
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引用次数: 54

摘要

本文描述了机器学习(ML)技术在一个现实世界问题中的应用:乳腺活检图像的自动诊断(分类)。应用的技术是遗传算法(GA)和基于案例的推理(CBR)。本文将我们的结果与以前使用神经网络(NN)得到的结果进行了比较。主要目标是:有效地解决这种类型的分类问题,并比较机器学习的不同替代方案。本文还介绍了我们为解决这类分类问题而开发的系统:GA方法的基于遗传的分类器系统(GeB-CS)和CBR方法的基于案例的分类器系统(CaB-CS)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic diagnosis with genetic algorithms and case-based reasoning

This article describes the application of Machine Learning (ML) techniques to a real world problem: the Automatic Diagnosis (classification) of Mammary Biopsy Images. The techniques applied are Genetic Algorithms (GA) and Case-Based Reasoning (CBR). The article compares our results with previous results obtained using Neural Networks (NN). The main goals are: to efficiently solve classification problems of such a type and to compare different alternatives for Machine Learning. The article also introduces the systems we developed for solving this kind of classification problems: Genetic Based Classifier System (GeB-CS) for a GA approach, and Case-Based Classifier System (CaB-CS) for a CBR approach.

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