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Comparing the performance of meta-classifiers—a case study on selected imbalanced data sets relevant for prediction of liver toxicity
ABSTRACT: Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to w...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919997/ https://www.ncbi.nlm.nih.gov/pubmed/29626291 http://dx.doi.org/10.1007/s10822-018-0116-z |