The Krypteia ensemble: designing classifier ensembles using an ancient Spartan military tradition
Fecha
2023Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Impacto
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10.1016/j.inffus.2022.09.021
Resumen
In this work we propose a new algorithm to train and optimize an ensemble of classifiers. We call this algorithm the Krypteia ensemble, based on an ancient Spartan tradition designed to convert their most promising individuals into future leaders of their society. We show how to adapt this ancient custom to optimize classifiers by generating different variations of the same task, each one offerin ...
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In this work we propose a new algorithm to train and optimize an ensemble of classifiers. We call this algorithm the Krypteia ensemble, based on an ancient Spartan tradition designed to convert their most promising individuals into future leaders of their society. We show how to adapt this ancient custom to optimize classifiers by generating different variations of the same task, each one offering different hardships according to distinct stochastic variables. This is thus applied to induce diversity in the set of individual weak learners. Then, we use a set of agents designed to select those subjects who excel in their assignments, and whose interaction minimizes excessive redundancies in the resulting population. We also study how different Krypteia ensembles can be stacked together, so that more complex classifiers can be built using the same procedure. Besides, we consider a wide range of different aggregation functions in the decision making phase to find the optimal performance for the different Krypteia ensemble variations tested. Finally, we study how different Krypteia ensembles perform for a wide range of classification datasets and we compare them with other state-of-the-art design techniques of classifier ensembles, obtaining favourable results to our proposal. [--]
Materias
Classifier ensemble,
Human social behaviour,
Krypteia,
Multi-agent systems,
Optimal classifier selection,
Social network,
Sparta
Editor
Elsevier
Publicado en
Information Fusion, 90 (2023), 283-297
Departamento
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Versión del editor
Entidades Financiadoras
Javier Fumanal Idocin and Humberto Bustince's research has been supported by project PID2019-108392 GB I00 (AEI/10.13039/ 501100011033). Oscar Cordón's research has been funded by the Spanish Ministry of Science and Innovation (MICIN), Agencia Estatal de Investigación (AEI), Spain, under grant CONFIA (PID2021-122916NB-I00), and by the Regional Government of Andalusia under grant EXAISFI (P18-FR-4262), both including European Regional Development Funds (ERDF). Open access funding provided by Universidad Pública de Navarra.