Use of Dempster-Shafer theory to combine classifiers which use different class boundaries

M. R. Ahmadzadeh; M. Petrou

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Use of Dempster-Shafer theory to combine classifiers which use different class boundaries

机译：使用Dempster-Shafer理论组合使用不同类别边界的分类器

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In this paper we present the Dempster-Shafer theory as a framework within which the results of a Baye-sian network classifier and a fuzzy logic-based classifier are combined to produce a better final classification. We deal with the case when the two original classifiers use different classes for the outcome. The problem of different classes is solved by using a superset of finer classes which can be combined to produce classes according to either of the two classifiers. Within the Dempster-Shafer formalism not only can the problem of different number of classes be solved, but the relative reliability of the classifiers can also be considered.

机译：在本文中，我们将Dempster-Shafer理论作为框架，在其中将贝叶斯网络分类器和基于模糊逻辑的分类器的结果相结合以产生更好的最终分类。我们处理两个原始分类器使用不同类别的结果时的情况。通过使用细类的超集来解决不同类的问题，这些细类可以根据两个分类器中的任何一个进行组合以生成类。在Dempster-Shafer形式主义中，不仅可以解决不同类别的问题，而且还可以考虑分类器的相对可靠性。

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来源
《Pattern Analysis and Applications》 |2003年第1期|p.41-46|共6页
作者
M. R. Ahmadzadeh; M. Petrou;
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作者单位

School of Electronic Technology, Shiraz University, Shiraz;

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收录信息美国《科学引文索引》(SCI);
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
bayesian networks; classifier combination; dempster-shafer theory; expert rules; fuzzy logic;

机译：贝叶斯网络;分类器组合;Dempster-shafer理论;专家规则;模糊逻辑;

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Use of Dempster-Shafer theory to combine classifiers which use different class boundaries

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