信念函数框架中一类分类器的融合

2007 10th International Conference on Information Fusion Pub Date : 2007-07-09 DOI:10.1109/ICIF.2007.4408102

Astride Aregui, T. Denoeux

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引用次数: 19

摘要

提出了一种将一类支持向量机(svm)或核主成分分析(KPCA)产生的新颖性度量转换为定义良好的识别框架上的信念函数的方法。这使得将单类分类或新颖性检测方法与在同一框架中表达的其他信息(如专家意见或多类分类器)结合起来成为可能。

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Fusion of one-class classifiers in the belief function framework

A method is proposed for converting a novelty measure such as produced by one-class SVMs or Kernel principal component analysis (KPCA) into a belief function on a well- defined frame of discernment. This makes it possible to combine one-class classification or novelty detection methods with other information expressed in the same framework such as expert opinions or multi-class classifiers.

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2007 10th International Conference on Information Fusion

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