粗糙支持向量机的精度和召回率

P. Lingras, C. Butz
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引用次数: 26

摘要

粗糙支持向量机(rsvm)通过提供更好的边界区域表示来补充传统支持向量机(svm)。人们对rsvm的理论发展越来越感兴趣,这已经导致将现有的SVM实现修改为rsvm。本文展示了如何将精度和召回率的使用从支持向量机实现扩展到RSVM实现。我们的方法在Gist(一种流行的支持向量机实现)的帮助下进行了实践验证。
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Precision and Recall in Rough Support Vector Machines
Rough support vector machines (RSVMs) supplement conventional support vector machines (SVMs) by providing a better representation of the boundary region. Increasing interest has been paid to the theoretical development of RSVMs, which has already lead to a modification of existing SVM implementations as RSVMs. This paper shows how to extend the use of precision and recall from a SVM implementation to a RSVM implementation. Our approach is demonstrated in practice with the help of Gist, a popular SVM implementation.
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