QuantificationLib: A Python library for quantification and prevalence estimation
Subject:
Quantification learning
Prevalence estimation
Ordinal quantification
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Elsevier
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Abstract:
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.
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.
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This work was supported by grant PID2019-110742RB-I00 from Spanish Ministerio de Economía y Competitividad (MINECO) and grant PID2019-109238GB-C21 from Spanish Ministry of Science and Innovation.
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