Homogeneous Ensemble Learning
Homogeneous Ensemble Learning is an ensemble learning approach in which multiple instances of the same type of base learner are combined to improve predictive performance, differing from heterogeneous ensembles by employing a uniform class of models across the ensemble.
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Publications
2K
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126
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59
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2017–2026
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Ensemble feature selection: Homogeneous and heterogeneous approaches
Borja Seijo-Pardo, Iago Porto-Díaz, Verónica Bolón‐Canedo et al. · Knowledge-Based Systems · 2016 · 299 citations
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Vellore Institute of Technology University, India
1 publications · 85 citations
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Annamalai University
Chidambaram, India
2 h-index
3 publications
204 citations

University of East Anglia
Norwich, United Kingdom
2 h-index
5 publications
457 citations

University of Energy and Natural Resources
Sunyani, Ghana
1 h-index
3 publications
264 citations

University of Essex
Colchester, United Kingdom
1 h-index
1 publications
19 citations

University of Tehran
Tehran, Iran
1 h-index
1 publications
25 citations
IPB University
Bogor, Indonesia
1 h-index
1 publications
10 citations
Jain University
Bengaluru, India
1 h-index
1 publications
85 citations

University of Sciences and Technology Houari Boumediene
Algiers, Algeria
1 h-index
3 publications
69 citations
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Repository · 2 publications · 59 citations
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1 publications · 154 citations
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1 publications · 17 citations
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1 publications · 113 citations
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1 publications · 37 citations
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