Ensemble Generation
Ensemble Generation is a methodological framework in machine learning that systematically constructs a collection of diverse base learners and combines their predictions to improve overall model accuracy and robustness, distinguished from other modeling approaches by its explicit focus on leveraging multiple heterogeneous or homogeneous models through strategic aggregation mechanisms.
357
Publications
33.2K
Citations
1.1K
Authors
483
Institutions
Publications per year
2017–2026
152
Parents
357
Ensemble based systems in decision making
Robi Polikar · IEEE Circuits and Systems Magazine · 2006 · 2.9K citations
An Ensemble Adjustment Kalman Filter for Data Assimilation
J. G. Anderson · Monthly Weather Review · 2001 · 1.8K citations · Full text
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483
Universität Hamburg
Hamburg, Germany
8 h-index
63 publications
2.6K citations
Nanjing University
Nanjing, China
8 h-index
22 publications
1.4K citations

École de Technologie Supérieure
Montreal, Canada
8 h-index
17 publications
1.2K citations

European Centre for Medium-Range Weather Forecasts
Reading, United Kingdom
7 h-index
15 publications
2.5K citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
16 publications
2.9K citations
Pontifícia Universidade Católica do Paraná
Curitiba, Brazil
6 h-index
12 publications
216 citations
Universidade Federal do Rio Grande do Norte
Natal, Brazil
6 h-index
19 publications
604 citations

Universidade Federal de Pernambuco
Recife, Brazil
6 h-index
11 publications
725 citations
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12 publications · 3.6K citations
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Repository · 14 publications · 315 citations
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9 publications · 975 citations
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8 publications · 350 citations
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TKDE · 8 publications · 938 citations
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