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Tree-Weighting for Multi-Study Ensemble Learners
Multi-study learning uses multiple training studies, separately trains classifiers on each, and forms an ensemble with weights rewarding members with better cross-study prediction ability. This article considers novel weighting approaches for constructing tree-based ensemble learners in this setting...
Autores principales: | Ramchandran, Maya, Patil, Prasad, Parmigiani, Giovanni |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980320/ https://www.ncbi.nlm.nih.gov/pubmed/31797618 |
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