| |  Online-Ressource |
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| Verfasst von: | Röder, Jens [VerfasserIn]  |
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| | Tolosana-Delgado, Raimon [VerfasserIn] |
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| | Hamprecht, Fred [VerfasserIn] |
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| Titel: | Gaussian process classification |
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| Titelzusatz: | singly versus doubly stochastic models, and new computational schemes |
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| Verf.angabe: | Jens Röder, Raimon Tolosana-Delgado, Fred A. Hamprecht |
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| E-Jahr: | 2011 |
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| Jahr: | 29 May 2011 |
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| Umfang: | 15 S. |
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| Fussnoten: | Gesehen am 19.09.2022 |
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| Titel Quelle: | Enthalten in: Stochastic environmental research and risk assessment |
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| Ort Quelle: | Berlin : Springer, 1987 |
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| Jahr Quelle: | 2011 |
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| Band/Heft Quelle: | 25(2011), 7, Seite 865-879 |
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| ISSN Quelle: | 1436-3259 |
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| | 1435-151X |
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| Abstract: | The aim of this paper is to compare four different methods for binary classification with an underlying Gaussian process with respect to theoretical consistency and practical performance. Two of the inference schemes, namely classical indicator kriging and simplicial indicator kriging, are analytically tractable and fast. However, these methods rely on simplifying assumptions which are inappropriate for categorical class labels. A consistent and previously described model extension involves a doubly stochastic process. There, the unknown posterior class probability f(·) is considered a realization of a spatially correlated Gaussian process that has been squashed to the unit interval, and a label at position x is considered an independent Bernoulli realization with success parameter f(x). Unfortunately, inference for this model is not known to be analytically tractable. In this paper, we propose two new computational schemes for the inference in this doubly stochastic model, namely the “Aitchison Maximum Posterior” and the “Doubly Stochastic Gaussian Quadrature”. Both methods are analytical up to a final step where optimization or integration must be carried out numerically. For the comparison of practical performance, the methods are applied to storm forecasts for the Spanish coast based on wave heights in the Mediterranean Sea. While the error rate of the doubly stochastic models is slightly lower, their computational cost is much higher. |
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| DOI: | doi:10.1007/s00477-011-0498-0 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1007/s00477-011-0498-0 |
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| | DOI: https://doi.org/10.1007/s00477-011-0498-0 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Classical indicator kriging |
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| | Doubly stochastic Gaussian quadrature |
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| | Doubly stochastic process Aitchison maximum posterior |
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| | Logistic transformation |
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| | Model-based geostatistics |
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| | Simplicial indicator kriging |
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| K10plus-PPN: | 1816926116 |
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| Verknüpfungen: | → Zeitschrift |
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Gaussian process classification / Röder, Jens [VerfasserIn]; 29 May 2011 (Online-Ressource)
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