Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data
Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data
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Dordrecht: Springer
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English
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Dordrecht: Springer
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In biological data, it is often the case that objects are described in two or more representations. In order to perform classification based on such data, we have to combine them in a certain way. In the context of kernel machines, this task amounts to mix several kernel matrices into one. In this paper, we present two ways to mix kernel matrices,...
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Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data
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TN_cdi_proquest_journals_2918338187
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918338187
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ISSN
1370-4621
E-ISSN
1573-773X
DOI
10.1023/B:NEPL.0000016845.36307.d7
