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MetaQuant: A framework for metaheuristic based quantification

delete2025-07-08
delete0
PRE
AI
Z
Zahra Donyavi
G
Gustavo Batista
DOI：10.1016/j.asoc.2025.113527delete
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Abstract

Abstract

En 中文
• A novel category of quantification methods is presented based on stochastic optimization. • A framework for metaheuristic-based quantification is proposed. • Ordinal Least Squared Linear Regression is suggested as a loss/fitness function for metaheuristic quantification. • Extensive experiments with several nature-inspired algorithms are evaluated. • Metaheuristic-based quantification outperforms the main state-of-the-art quantifiers.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

No organization information available