OmniGA: Optimized Omnivariate Decision Trees for Generalizable Classification Models
Abstract Classification problems from different domains vary in complexity, size, and imbalance of the number of samples from different classes. Although several classification models have been proposed, selecting the right model and parameters for a given classification task to achieve good perform...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2017
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/364ca4f44c504fb6a0a83037a7d7273f |
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