Zielonogórska Biblioteka Cyfrowa udostępnia 65 553 obiektów cyfrowych
Obiekt
Tytuł: Revisiting strategies for fitting logistic regression for positive and unlabeled data
Contributor:
Witczak, Marcin - ed. ; Stetter, Ralf - ed.
Subtitle:
Group publication title:
Abstract:
Positive unlabeled (PU) learning is an important problem motivated by the occurrence of this type of partial observability in many applications. The present paper reconsiders recent advances in parametric modeling of PU data based on empirical likelihood maximization and argues that they can be significantly improved. The proposed approach is based on the fact that the likelihood for the logistic fit and an unknown labeling frequency can be expressed as the sum of a convex and a concave function, which is explicitly given. ; This allows methods such as the concave-convex procedure (CCCP) or its variant, the disciplined convex-concave procedure (DCCP), to be applied. We show by analyzing real data sets that, by using the DCCP to solve the optimization problem, we obtain significant improvements in the posterior probability and the label frequency estimation over the best available competitors.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
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DOI:
Pages:
Source:
AMCS, volume 32, number 2 (2022) ; kliknij tutaj, żeby przejść
Language:
License CC BY 4.0:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2022)
Data ostatniej modyfikacji:
Jul 23, 2025
Data dodania obiektu:
Jul 23, 2025
Liczba wyświetleń treści obiektu:
17
Wszystkie dostępne wersje tego obiektu:
https://zbc.uz.zgora.pl/publication/101479
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 32, number 1 (2022)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 32, number 2 (2022)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 32, number 3 (2022)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 32, number 4 (2022)
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| Nazwa wydania | Data |
|---|---|
| Revisiting strategies for fitting logistic regression for positive and unlabeled data | Jul 23, 2025 |
Obiekty Podobne
Mielniczuk, Jan Wawrzeńczyk, Adam Korbicz, Józef (1951- ) - red. Uciński, Dariusz - red.
Merino, Javier Antón
Teisseyre, Paweł Witczak, Marcin - ed. Stetter, Ralf - ed.
