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OmniGA: Optimized Omnivariate Decision Trees for Generalizable Classification Models
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 performance is n...
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| Veröffentlicht in: | Sci Rep |
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| Hauptverfasser: | , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Publishing Group UK
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5478657/ https://ncbi.nlm.nih.gov/pubmed/28634344 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-017-04281-9 |
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