QuantificationLib: A Python library for quantification and prevalence estimation

QuantificationLib is an open-source Python library that provides a comprehensive set of algorithms for quantification learning. Quantification, also known as prevalence estimation, is a supervised machine-learning task where the objective is to train a model that is able to predict the distribution...

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Detalles Bibliográficos
Autores: Castaño Gutiérrez, Alberto|||0000-0002-3946-5820, Alonso González, Jaime|||0000-0001-9718-4683, González González, Pablo|||0000-0002-9250-0920, Pérez Núñez, Pablo, Coz Velasco, Juan José del|||0000-0002-4288-3839
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad de Oviedo (UNIOVI)
Repositorio:RUO. Repositorio Institucional de la Universidad de Oviedo
Idioma:inglés
OAI Identifier:oai:digibuo.uniovi.es:10651/72372
Acceso en línea:https://hdl.handle.net/10651/72372
https://dx.doi.org/10.1016/j.softx.2024.101728
Access Level:acceso abierto
Palabra clave:Quantification learning
Prevalence estimation
Ordinal quantification
Descripción
Sumario:QuantificationLib is an open-source Python library that provides a comprehensive set of algorithms for quantification learning. Quantification, also known as prevalence estimation, is a supervised machine-learning task where the objective is to train a model that is able to predict the distribution of classes in a set of unseen examples or bags. This library offers a wide variety of quantification methods suited for easy prototyping and experimentation, applicable to a wide range of quantification applications.