On Using Asymmetry Information for Classification in Extended Dissimilarity Spaces
作者： Yenisel Plasencia-Calaña , Edel B. García-Reyes , Robert P. W. Duin , Mauricio Orozco-Alzate
DOI: 10.1007/978-3-642-33275-3_62
关键词:
摘要: When asymmetric dissimilarity measures arise, asymmetry correction methods such as averaging are used in order to make the matrix symmetric. This is usually needed for application of pattern recognition procedures, but this way information lost. In paper we present a new approach use spaces. We show that taking into account improves classification accuracy when small number prototypes create an extended space. If degree higher, improvements also higher. The symmetrization by works well general, decreases performance highly data.
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sci-hub.st 参考文章(15)
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