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Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications
Ensemble learning helps improve machine learning results by combining several models and allows the production of better predictive performance compared to a single model. It also benefits and accelerates the researches in quantitative structure–activity relationship (QSAR) and quantitative structur...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106596/ https://www.ncbi.nlm.nih.gov/pubmed/33430997 http://dx.doi.org/10.1186/s13321-020-0417-9 |