Learning localized rule mixtures by maximizing the area under the ROC curve, 
with an application to the prediction of HIV-1 coreceptor usage

Sing, Tobias

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Learning localized rule mixtures by maximizing the area under the ROC curve, with an application to the prediction of HIV-1 coreceptor usage

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Sing, Tobias
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Sing, T. (2004). Learning localized rule mixtures by maximizing the area under the ROC curve, with an application to the prediction of HIV-1 coreceptor usage. Master Thesis, Albert-Ludwigs-Universität, Freiburg.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-2AD0-C

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