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

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.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-2AD0-C Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-A822-1

Genre: Thesis

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Creators:
Sing, Tobias¹, Author

Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046

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Language(s): eng - English

Dates: Accepted: 2004Date issued: 2004

Publication Status: Issued

Pages: -

Publishing info: Freiburg : Albert-Ludwigs-Universität

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Rev. Type: -

Identifiers: eDoc: 232012
Other: Local-ID: C125673F004B2D7B-CADB1B353BE24C44C1256FB70051E86E-Sing2004a

Degree: Master

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