Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models

Ensembles are a widely implemented approach in the machine learning community and their success is traditionally attributed to the diversity within the ensemble. Most of these approaches foster diversity in the ensemble by data sampling or by modifying the structure of the constituent models. Despit...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2022-08, Vol.33 (8), p.4031-4042
Hauptverfasser:	Perales-Gonzalez, Carlos, Fernandez-Navarro, Francisco, Carbonero-Ruz, Mariano, Perez-Rodriguez, Javier
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Basis functions Correlation Data models Data sampling Ensemble Error functions Estimation Exact solutions Global optimization Learning systems Machine learning negative correlation learning (NCL) Neural networks Optimization Training Training data
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